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Upstream sync 2024 03 18 (#134)
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SUMMARY:
* upstream merge (sync) up to `93348d9458af7517bb8c114611d438a1b4a2c3be`
* some minor changes related to `ruff` and `yapf`

NOTES: skipped flaky lora gemma test

TEST PLAN:
ran nightly, passed all except gemma
running now on remote push

---------

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15 changes: 8 additions & 7 deletions .buildkite/test-pipeline.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,7 @@ steps:

- label: Basic Correctness Test
command: pytest -v -s --forked basic_correctness

- label: Core Test
command: pytest -v -s core

Expand All @@ -28,14 +28,14 @@ steps:
num_gpus: 2 # only support 1 or 2 for now.

- label: Engine Test
command: pytest -v -s engine test_sequence.py
command: pytest -v -s engine tokenization test_sequence.py

- label: Entrypoints Test
command: pytest -v -s entrypoints

- label: Kernels Test
command: pytest -v -s kernels
soft_fail: true
- label: Kernels Test %N
command: pytest -v -s kernels --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
parallelism: 4

- label: Models Test
commands:
Expand All @@ -55,8 +55,9 @@ steps:
- label: Speculative decoding tests
command: pytest -v -s spec_decode

- label: LoRA Test
command: pytest -v -s lora --forked
- label: LoRA Test %N
command: pytest -v -s lora --forked --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
parallelism: 4

- label: Metrics Test
command: pytest -v -s metrics
Expand Down
3 changes: 3 additions & 0 deletions .buildkite/test-template.j2
Original file line number Diff line number Diff line change
Expand Up @@ -20,6 +20,9 @@ steps:
agents:
queue: kubernetes
soft_fail: {{ step.soft_fail or false }}
{% if step.parallelism %}
parallelism: {{ step.parallelism }}
{% endif %}
retry:
automatic:
- exit_status: -1 # Agent was lost
Expand Down
2 changes: 1 addition & 1 deletion .github/ISSUE_TEMPLATE/100-documentation.yml
Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
name: 📚 Documentation
description: Report an issue related to https://docs.vllm.ai/
title: "[Doc]: "
labels: ["doc"]
labels: ["documentation"]

body:
- type: textarea
Expand Down
2 changes: 1 addition & 1 deletion .github/ISSUE_TEMPLATE/500-feature request.yml
Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
name: 🚀 Feature request
description: Submit a proposal/request for a new vllm feature
title: "[Feature]: "
labels: ["feature"]
labels: ["feature request"]

body:
- type: markdown
Expand Down
60 changes: 60 additions & 0 deletions .github/PULL_REQUEST_TEMPLATE.md
Original file line number Diff line number Diff line change
@@ -0,0 +1,60 @@
<details>
<!-- inside this <details> section, markdown rendering does not work, so we use raw html here. -->
<summary><b> PR Checklist (Click to expand. Please read before submitting.) </b></summary>

<p>Thank you for your contribution to vLLM! Before submitting the pull request, please ensure the PR meets the following criteria. This helps vLLM maintain the code quality and improve the efficiency of the review process.</p>

<h3>PR Title and Classification</h3>
<p>Only specific types of PRs will be reviewed. The PR title is prefixed appropriately to indicate the type of change. Please use one of the following:</p>
<ul>
<li><code>[Bugfix]</code> for bug fixes.</li>
<li><code>[CI/Build]</code> for build or continuous integration improvements.</li>
<li><code>[Doc]</code> for documentation fixes and improvements.</li>
<li><code>[Model]</code> for adding a new model or improving an existing model. Model name should appear in the title.</li>
<li><code>[Frontend]</code> For changes on the vLLM frontend (e.g., OpenAI API server, <code>LLM</code> class, etc.) </li>
<li><code>[Kernel]</code> for changes affecting CUDA kernels or other compute kernels.</li>
<li><code>[Core]</code> for changes in the core vLLM logic (e.g., <code>LLMEngine</code>, <code>AsyncLLMEngine</code>, <code>Scheduler</code>, etc.)</li>
<li><code>[Hardware][Vendor]</code> for hardware-specific changes. Vendor name should appear in the prefix (e.g., <code>[Hardware][AMD]</code>).</li>
<li><code>[Misc]</code> for PRs that do not fit the above categories. Please use this sparingly.</li>
</ul>
<p><strong>Note:</strong> If the PR spans more than one category, please include all relevant prefixes.</p>

<h3>Code Quality</h3>

<p>The PR need to meet the following code quality standards:</p>

<ul>
<li>We adhere to <a href="https://google.github.io/styleguide/pyguide.html">Google Python style guide</a> and <a href="https://google.github.io/styleguide/cppguide.html">Google C++ style guide</a>.</li>
<li>Pass all linter checks. Please use <a href="https://github.com/vllm-project/vllm/blob/main/format.sh"><code>format.sh</code></a> to format your code.</li>
<li>The code need to be well-documented to ensure future contributors can easily understand the code.</li>
<li>Include sufficient tests to ensure the project to stay correct and robust. This includes both unit tests and integration tests.</li>
<li>Please add documentation to <code>docs/source/</code> if the PR modifies the user-facing behaviors of vLLM. It helps vLLM user understand and utilize the new features or changes.</li>
</ul>

<h3>Notes for Large Changes</h3>
<p>Please keep the changes as concise as possible. For major architectural changes (>500 LOC excluding kernel/data/config/test), we would expect a GitHub issue (RFC) discussing the technical design and justification. Otherwise, we will tag it with <code>rfc-required</code> and might not go through the PR.</p>

<h3>What to Expect for the Reviews</h3>

<p>The goal of the vLLM team is to be a <i>transparent reviewing machine</i>. We would like to make the review process transparent and efficient and make sure no contributor feel confused or frustrated. However, the vLLM team is small, so we need to prioritize some PRs over others. Here is what you can expect from the review process: </p>

<ul>
<li> After the PR is submitted, the PR will be assigned to a reviewer. Every reviewer will pick up the PRs based on their expertise and availability.</li>
<li> After the PR is assigned, the reviewer will provide status update every 2-3 days. If the PR is not reviewed within 7 days, please feel free to ping the reviewer or the vLLM team.</li>
<li> After the review, the reviewer will put an <code> action-required</code> label on the PR if there are changes required. The contributor should address the comments and ping the reviewer to re-review the PR.</li>
<li> Please respond to all comments within a reasonable time frame. If a comment isn't clear or you disagree with a suggestion, feel free to ask for clarification or discuss the suggestion.
</li>
</ul>

<h3>Thank You</h3>

<p> Finally, thank you for taking the time to read these guidelines and for your interest in contributing to vLLM. Your contributions make vLLM a great tool for everyone! </p>


</details>

---

Please provide a brief explanation of the motivation behind the PR and the changes it introduces. This helps reviewers understand the context and rationale for the contribution. If possible, please link existing issues this PR will resolve.


4 changes: 2 additions & 2 deletions .github/workflows/ruff.yml
Original file line number Diff line number Diff line change
Expand Up @@ -28,7 +28,7 @@ jobs:
pip install ruff==0.1.5 codespell==2.2.6 tomli==2.0.1
- name: Analysing the code with ruff
run: |
ruff vllm tests
ruff .
- name: Spelling check with codespell
run: |
codespell --toml pyproject.toml
codespell --toml pyproject.toml
26 changes: 2 additions & 24 deletions CONTRIBUTING.md
Original file line number Diff line number Diff line change
Expand Up @@ -45,31 +45,9 @@ pytest tests/
If you encounter a bug or have a feature request, please check our issues page first to see if someone else has already reported it.
If not, please file a new issue, providing as much relevant information as possible.

### Coding Style Guide
### Pull Requests & Code Reviews

In general, we adhere to [Google Python style guide](https://google.github.io/styleguide/pyguide.html) and [Google C++ style guide](https://google.github.io/styleguide/cppguide.html).

We include a formatting script [`format.sh`](./format.sh) to format the code.

### Pull Requests

When submitting a pull request:

1. Make sure your code has been rebased on top of the latest commit on the main branch.
2. Ensure code is properly formatted by running [`format.sh`](./format.sh).
3. Include a detailed description of the changes in the pull request.
Explain why you made the changes you did.
If your pull request fixes an open issue, please include a reference to it in the description.

### Code Reviews

All submissions, including submissions by project members, require a code review.
To make the review process as smooth as possible, please:

1. Keep your changes as concise as possible.
If your pull request involves multiple unrelated changes, consider splitting it into separate pull requests.
2. Respond to all comments within a reasonable time frame.
If a comment isn't clear or you disagree with a suggestion, feel free to ask for clarification or discuss the suggestion.
Please check the PR checklist in the [PR template](.github/PULL_REQUEST_TEMPLATE.md) for detailed guide for contribution.

### Thank You

Expand Down
21 changes: 15 additions & 6 deletions benchmarks/backend_request_func.py
Original file line number Diff line number Diff line change
Expand Up @@ -68,7 +68,7 @@ async def async_request_tgi(
output.ttft = ttft
output.latency = time.perf_counter() - st

body = data.decode("utf-8").lstrip("data:") # noqa
body = remove_prefix(data.decode("utf-8"), "data:")
output.generated_text = json.loads(body)["generated_text"]
output.success = True
else:
Expand Down Expand Up @@ -114,7 +114,7 @@ async def async_request_vllm(
output.ttft = ttft
output.latency = time.perf_counter() - st

# When streaming, '\0' is appended to the end of the response.
# When streaming, '\0' is appended to the end of response.
body = data.decode("utf-8").strip("\0")
output.generated_text = json.loads(
body)["text"][0][len(request_func_input.prompt):]
Expand Down Expand Up @@ -162,7 +162,7 @@ async def async_request_trt_llm(
output.ttft = ttft
output.latency = time.perf_counter() - st

body = data.decode("utf-8").lstrip("data:") # noqa
body = remove_prefix(data.decode("utf-8"), "data:")
output.generated_text = json.loads(body)["text_output"]
output.success = True

Expand Down Expand Up @@ -196,7 +196,8 @@ async def async_request_deepspeed_mii(
output = RequestFuncOutput()
output.prompt_len = request_func_input.prompt_len

# DeepSpeed-MII doesn't support streaming as of Jan 28 2024, will use 0 as placeholder.
# DeepSpeed-MII doesn't support streaming as of Jan 28 2024,
# will use 0 as placeholder.
# https://github.com/microsoft/DeepSpeed-MII/pull/311
output.ttft = 0

Expand Down Expand Up @@ -259,7 +260,7 @@ async def async_request_openai_completions(
if not chunk:
continue

chunk = chunk.decode("utf-8").lstrip("data: ") # noqa
chunk = remove_prefix(chunk.decode("utf-8"), "data: ")
if chunk == "[DONE]":
latency = time.perf_counter() - st
else:
Expand Down Expand Up @@ -326,7 +327,7 @@ async def async_request_openai_chat_completions(
if not chunk:
continue

chunk = chunk.decode("utf-8").lstrip("data: ")
chunk = remove_prefix(chunk.decode("utf-8"), "data: ")
if chunk == "[DONE]":
latency = time.perf_counter() - st
else:
Expand All @@ -348,6 +349,14 @@ async def async_request_openai_chat_completions(
return output


# Since vllm must support Python 3.8, we can't use str.removeprefix(prefix)
# introduced in Python 3.9
def remove_prefix(text: str, prefix: str) -> str:
if text.startswith(prefix):
return text[len(prefix):]
return text


ASYNC_REQUEST_FUNCS = {
"tgi": async_request_tgi,
"vllm": async_request_vllm,
Expand Down
6 changes: 4 additions & 2 deletions benchmarks/benchmark_serving.py
Original file line number Diff line number Diff line change
Expand Up @@ -295,7 +295,9 @@ def main(args: argparse.Namespace):

# Save to file
base_model_id = model_id.split("/")[-1]
file_name = f"{backend}-{args.request_rate}qps-{base_model_id}-{current_dt}.json"
file_name = (
f"{backend}-{args.request_rate}qps-{base_model_id}-{current_dt}.json"
)
with open(file_name, "w") as outfile:
json.dump(result_json, outfile)

Expand Down Expand Up @@ -343,7 +345,7 @@ def main(args: argparse.Namespace):
"--tokenizer",
type=str,
help=
"Name or path of the tokenizer, if not using the default model tokenizer.",
"Name or path of the tokenizer, if not using the default tokenizer.",
)
parser.add_argument(
"--best-of",
Expand Down
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Benchmark suite Current: 7ab58f7 Previous: f90ec1c Ratio
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 256,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 14.894920580211929 prompts/s 14.102493680612561 prompts/s 0.95
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 256,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3827.9945891144657 tokens/s 3624.340875917428 tokens/s 0.95
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2048,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2.0868383653123574 prompts/s 1.956063305083001 prompts/s 0.94
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2048,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4275.93181052502 tokens/s 4007.973712115069 tokens/s 0.94
{"name": "request_throughput", "description": "VLLM Engine decode throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 64,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 16.50499928318026 prompts/s 15.888657444497307 prompts/s 0.96
{"name": "token_throughput", "description": "VLLM Engine decode throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 64,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2145.649906813434 tokens/s 2065.5254677846497 tokens/s 0.96
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 64,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 23.554525876591278 prompts/s 22.87289352391561 prompts/s 0.97
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 64,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1531.044181978433 tokens/s 1486.7380790545146 tokens/s 0.97
{"name": "request_throughput", "description": "VLLM Engine decode throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 32,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 10.778850096447076 prompts/s 10.489840268440735 prompts/s 0.97
{"name": "token_throughput", "description": "VLLM Engine decode throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 32,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1401.25051253812 tokens/s 1363.6792348972956 tokens/s 0.97
{"name": "request_throughput", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 0.491929678590423 prompts/s 0.49193518625872273 prompts/s 1.00
{"name": "input_throughput", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 130.03669123859243 tokens/s 130.03814713563077 tokens/s 1.00
{"name": "output_throughput", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 122.00839888399672 tokens/s 122.00976489588841 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 4\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3.7403566009210403 prompts/s 3.8232643960110053 prompts/s 1.02
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 4\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 486.2463581197352 tokens/s 497.0243714814307 tokens/s 1.02
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 4\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3.2053571672857335 prompts/s 3.201821841750221 prompts/s 1.00
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 4\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 416.69643174714537 tokens/s 416.2368394275287 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Engine decode throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 16,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 6.816094689330718 prompts/s 6.622269139435227 prompts/s 0.97
{"name": "token_throughput", "description": "VLLM Engine decode throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 16,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 886.0923096129934 tokens/s 860.8949881265796 tokens/s 0.97
{"name": "request_throughput", "description": "VLLM Engine decode throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 8,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4.162378681703445 prompts/s 4.0992486092617515 prompts/s 0.98
{"name": "token_throughput", "description": "VLLM Engine decode throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 8,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 541.1092286214479 tokens/s 532.9023192040277 tokens/s 0.98
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 128,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 23.928425868060163 prompts/s 23.20290431681759 prompts/s 0.97
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 128,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3086.766936979761 tokens/s 2993.1746568694693 tokens/s 0.97
{"name": "request_throughput", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4.411590816153445 prompts/s 4.224088551976798 prompts/s 0.96
{"name": "input_throughput", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1321.225862999523 tokens/s 1265.0708724020137 tokens/s 0.96
{"name": "output_throughput", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1002.4913675929807 tokens/s 959.9522840270738 tokens/s 0.96
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 256,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 14.95703002396225 prompts/s 14.04770956163205 prompts/s 0.94
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 256,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3843.9567161582986 tokens/s 3610.261357339437 tokens/s 0.94
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 512,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 7.4298214173654715 prompts/s 7.078806684221659 prompts/s 0.95
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 512,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3811.498387108487 tokens/s 3631.427829005711 tokens/s 0.95
{"name": "request_throughput", "description": "VLLM Engine throughput - Dense (with dataset)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"dataset\": \"sharegpt\",\n \"output-len\": 128,\n \"num-prompts\": 1000\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 6.487093714968206 prompts/s 6.172054502448429 prompts/s 0.95
{"name": "token_throughput", "description": "VLLM Engine throughput - Dense (with dataset)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"dataset\": \"sharegpt\",\n \"output-len\": 128,\n \"num-prompts\": 1000\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3057.7954160497034 tokens/s 2909.2966426011058 tokens/s 0.95
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2048,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2.1302544782386184 prompts/s 2.0248530585969813 prompts/s 0.95
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2048,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4364.891425910929 tokens/s 4148.923917065215 tokens/s 0.95
{"name": "request_throughput", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4.5470011375369745 prompts/s 4.419228710985807 prompts/s 0.97
{"name": "input_throughput", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1440.8991904740917 tokens/s 1400.4093862242921 tokens/s 0.97
{"name": "output_throughput", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1039.408084031852 tokens/s 1009.7554604780948 tokens/s 0.97
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2048,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2.102740471376283 prompts/s 1.959609462532708 prompts/s 0.93
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2048,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4308.515225850005 tokens/s 4015.2397887295188 tokens/s 0.93
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 8\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 5.200308965437526 prompts/s 5.091128955479468 prompts/s 0.98
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 8\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 676.0401655068785 tokens/s 661.8467642123309 tokens/s 0.98
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 32,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 33.919933355866185 prompts/s 33.00021704146777 prompts/s 0.97
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 32,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1119.357800743584 tokens/s 1089.0071623684364 tokens/s 0.97
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 32,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 10.702150803489737 prompts/s 10.419207640752157 prompts/s 0.97
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 32,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1391.2796044536658 tokens/s 1354.4969932977806 tokens/s 0.97
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 8\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 6.780430469395904 prompts/s 6.631816273208401 prompts/s 0.98
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 8\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 881.4559610214676 tokens/s 862.1361155170921 tokens/s 0.98
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 128,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 24.243161821544188 prompts/s 23.398470072064267 prompts/s 0.97
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 128,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3127.3678749792 tokens/s 3018.4026392962905 tokens/s 0.97
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 16,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 30.310248733626004 prompts/s 29.987869607534673 prompts/s 0.99
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 16,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 515.2742284716421 tokens/s 509.79378332808943 tokens/s 0.99
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 16\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 6.4785390647561485 prompts/s 6.520403642801777 prompts/s 1.01
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 16\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 842.2100784182993 tokens/s 847.6524735642311 tokens/s 1.01
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 1024,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3.833736241754914 prompts/s 3.6675738764901795 prompts/s 0.96
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 1024,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3929.579647798787 tokens/s 3759.263223402434 tokens/s 0.96
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 128,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 23.85637773717674 prompts/s 22.961842560923493 prompts/s 0.96
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 128,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3077.4727280957995 tokens/s 2962.077690359131 tokens/s 0.96
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 1024,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4.022373147369675 prompts/s 3.7925435014755324 prompts/s 0.94
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 1024,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4122.932476053917 tokens/s 3887.357089012421 tokens/s 0.94
{"name": "request_throughput", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 0.983936150743942 prompts/s 0.9839186075537723 prompts/s 1.00
{"name": "input_throughput", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 290.11685383402045 tokens/s 290.1116811659216 tokens/s 1.00
{"name": "output_throughput", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 212.40557664826392 tokens/s 212.39195035524912 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 64,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 35.530462520168584 prompts/s 34.67485612674781 prompts/s 0.98
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 64,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2309.4800638109577 tokens/s 2253.8656482386077 tokens/s 0.98
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 0.64102733645986 prompts/s 0.6386233475456284 prompts/s 1.00
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 83.33355373978179 tokens/s 83.0210351809317 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 16\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 6.75167893250834 prompts/s 6.651139711255816 prompts/s 0.99
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 16\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 877.7182612260842 tokens/s 864.6481624632561 tokens/s 0.99
{"name": "request_throughput", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4.379805484810321 prompts/s 4.2157844550337575 prompts/s 0.96
{"name": "input_throughput", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1282.288791204372 tokens/s 1234.2678622535984 tokens/s 0.96
{"name": "output_throughput", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1016.9528752587548 tokens/s 978.8812610135933 tokens/s 0.96
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 64\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 12.83963365850768 prompts/s 12.495041745355275 prompts/s 0.97
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 64\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1669.1523756059983 tokens/s 1624.3554268961857 tokens/s 0.97
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 32\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 14.156075211374656 prompts/s 13.531756847523814 prompts/s 0.96
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 32\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1840.2897774787054 tokens/s 1759.128390178096 tokens/s 0.96
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 32\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 9.563182715296602 prompts/s 9.431745225659517 prompts/s 0.99
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 32\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1243.213752988558 tokens/s 1226.1268793357372 tokens/s 0.99
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 256,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 13.392692245491206 prompts/s 12.637743505366036 prompts/s 0.94
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 256,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3441.92190709124 tokens/s 3247.900080879071 tokens/s 0.94
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 128,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 23.911792838152284 prompts/s 22.951713884791396 prompts/s 0.96
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 128,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3084.6212761216443 tokens/s 2960.77109113809 tokens/s 0.96
{"name": "request_throughput", "description": "VLLM Engine decode throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 1,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 0.6117085163530648 prompts/s 0.6117813849146969 prompts/s 1.00
{"name": "token_throughput", "description": "VLLM Engine decode throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 1,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 79.52210712589842 tokens/s 79.5315800389106 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 64,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 16.362376141339915 prompts/s 15.690996153602407 prompts/s 0.96
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 64,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2127.108898374189 tokens/s 2039.829499968313 tokens/s 0.96
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 8\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4.114968957144306 prompts/s 4.074032541201369 prompts/s 0.99
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 8\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 534.9459644287599 tokens/s 529.624230356178 tokens/s 0.99
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 8\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4.394611985973138 prompts/s 4.362329994915739 prompts/s 0.99
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 8\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 571.299558176508 tokens/s 567.1028993390461 tokens/s 0.99
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 256,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 12.158929119514804 prompts/s 11.615998417116817 prompts/s 0.96
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 256,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3124.8447837153044 tokens/s 2985.311593199022 tokens/s 0.96
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 16,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 6.751990065615257 prompts/s 6.6318419444524395 prompts/s 0.98
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 16,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 877.7587085299836 tokens/s 862.1394527788171 tokens/s 0.98
{"name": "request_throughput", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4.160822216572024 prompts/s 4.016810832190122 prompts/s 0.97
{"name": "input_throughput", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1318.5229522095087 tokens/s 1272.8871846127277 tokens/s 0.97
{"name": "output_throughput", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 945.9962175153822 tokens/s 915.7257547838227 tokens/s 0.97
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 0.9216644108282768 prompts/s 0.9433888430616232 prompts/s 1.02
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 119.81637340767598 tokens/s 122.64054959801102 tokens/s 1.02
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 64,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 34.02725106273189 prompts/s 32.89032910401961 prompts/s 0.97
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 64,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2211.771319077573 tokens/s 2137.8713917612745 tokens/s 0.97
{"name": "request_throughput", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4.825403175159669 prompts/s 4.609555875954635 prompts/s 0.96
{"name": "input_throughput", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1445.158388460844 tokens/s 1380.5143527710284 tokens/s 0.96
{"name": "output_throughput", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 969.7274982896124 tokens/s 924.5524507078491 tokens/s 0.95
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2048,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2.0207383159830203 prompts/s 1.9081044822228623 prompts/s 0.94
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2048,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4140.492809449209 tokens/s 3909.706084074645 tokens/s 0.94
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 64,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 33.4628524161056 prompts/s 32.345353148125646 prompts/s 0.97
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 64,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2175.085407046864 tokens/s 2102.447954628167 tokens/s 0.97
{"name": "request_throughput", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2.4035894049758784 prompts/s 2.399224266664285 prompts/s 1.00
{"name": "input_throughput", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 742.2925039740172 tokens/s 740.944432859709 tokens/s 1.00
{"name": "output_throughput", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 551.7038880887966 tokens/s 550.7115402387423 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Engine throughput - Dense (with dataset)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"dataset\": \"sharegpt\",\n \"output-len\": 128,\n \"num-prompts\": 1000\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 7.008971340409791 prompts/s 6.6883001323588065 prompts/s 0.95
{"name": "token_throughput", "description": "VLLM Engine throughput - Dense (with dataset)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"dataset\": \"sharegpt\",\n \"output-len\": 128,\n \"num-prompts\": 1000\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3277.1146399220015 tokens/s 3127.1816098856834 tokens/s 0.95
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 32\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 10.735589851326392 prompts/s 10.461344340638886 prompts/s 0.97
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 32\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1395.626680672431 tokens/s 1359.9747642830553 tokens/s 0.97
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 64\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 16.056155645714288 prompts/s 15.428244836595477 prompts/s 0.96
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 64\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2087.300233942857 tokens/s 2005.671828757412 tokens/s 0.96
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 128,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 21.104195570402688 prompts/s 20.06624992822618 prompts/s 0.95
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 128,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2722.4412285819467 tokens/s 2588.546240741178 tokens/s 0.95
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 64,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 33.35873601297494 prompts/s 32.44446213716631 prompts/s 0.97
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 64,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2168.317840843371 tokens/s 2108.8900389158102 tokens/s 0.97
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 16,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 36.4796017027384 prompts/s 36.11088250974342 prompts/s 0.99
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 16,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 620.1532289465528 tokens/s 613.8850026656381 tokens/s 0.99
{"name": "request_throughput", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 0.4917574418000191 prompts/s 0.4919457120660308 prompts/s 1.00
{"name": "input_throughput", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 129.99116216541705 tokens/s 130.0409295275346 tokens/s 1.00
{"name": "output_throughput", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 102.61994295482799 tokens/s 103.10854161095962 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Engine throughput - Sparse (with dataset)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"dataset\": \"sharegpt\",\n \"output-len\": 128,\n \"num-prompts\": 1000,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 6.914927098366293 prompts/s 6.546957496733268 prompts/s 0.95
{"name": "token_throughput", "description": "VLLM Engine throughput - Sparse (with dataset)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"dataset\": \"sharegpt\",\n \"output-len\": 128,\n \"num-prompts\": 1000,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3233.143314112144 tokens/s 3061.095447172607 tokens/s 0.95
{"name": "request_throughput", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2.424508514496617 prompts/s 2.416197396160986 prompts/s 1.00
{"name": "input_throughput", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 748.7528828369419 tokens/s 746.1861878650768 tokens/s 1.00
{"name": "output_throughput", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 553.3762887047466 tokens/s 551.5341040338195 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 4\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2.425477574446724 prompts/s 2.406570432068196 prompts/s 0.99
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 4\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 315.31208467807414 tokens/s 312.85415616886553 tokens/s 0.99
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 1,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 0.6106873227435267 prompts/s 0.6142763014135991 prompts/s 1.01
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 1,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 79.38935195665846 tokens/s 79.85591918376788 tokens/s 1.01
{"name": "request_throughput", "description": "VLLM Engine decode throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 4,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2.2211363197810177 prompts/s 2.238474883009656 prompts/s 1.01
{"name": "token_throughput", "description": "VLLM Engine decode throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 4,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 288.74772157153234 tokens/s 291.00173479125533 tokens/s 1.01
{"name": "request_throughput", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4.207076043162693 prompts/s 4.076611754150917 prompts/s 0.97
{"name": "input_throughput", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1336.7170759114445 tokens/s 1295.26457038754 tokens/s 0.97
{"name": "output_throughput", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 942.017615694007 tokens/s 912.7941378719316 tokens/s 0.97
{"name": "request_throughput", "description": "VLLM Engine throughput - synthetic\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 256,\n \"output-len\": 128,\n \"num-prompts\": 1000\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 8.879319409815679 prompts/s 8.315750611968816 prompts/s 0.94
{"name": "token_throughput", "description": "VLLM Engine throughput - synthetic\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 256,\n \"output-len\": 128,\n \"num-prompts\": 1000\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3409.6586533692202 tokens/s 3193.2482349960255 tokens/s 0.94
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 16,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 34.254667420932236 prompts/s 33.83223245430643 prompts/s 0.99
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 16,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 582.329346155848 tokens/s 575.1479517232093 tokens/s 0.99
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 16,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 34.45031117728038 prompts/s 34.54528439387231 prompts/s 1.00
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 16,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 585.6552900137666 tokens/s 587.2698346958292 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2.3746949187845043 prompts/s 2.3686518377204515 prompts/s 1.00
{"name": "input_throughput", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 774.4766682925949 tokens/s 772.5057939492475 tokens/s 1.00
{"name": "output_throughput", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 539.7839863391764 tokens/s 538.3756134991569 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2.453451421058017 prompts/s 2.4526082433675502 prompts/s 1.00
{"name": "input_throughput", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 757.6912241939439 tokens/s 757.4308284383893 tokens/s 1.00
{"name": "output_throughput", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 563.2699197836224 tokens/s 563.0632602236732 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 8,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4.161121391588271 prompts/s 4.115921591561094 prompts/s 0.99
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 8,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 540.9457809064752 tokens/s 535.0698069029421 tokens/s 0.99
{"name": "request_throughput", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 0.491895184081518 prompts/s 0.49188736088344975 prompts/s 1.00
{"name": "input_throughput", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 130.02757296010847 tokens/s 130.0255049759311 tokens/s 1.00
{"name": "output_throughput", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 122.00640215835251 tokens/s 121.99134474816809 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 0.9839477463520429 prompts/s 0.9839527814068058 prompts/s 1.00
{"name": "input_throughput", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 290.120272837721 tokens/s 290.1217574404014 tokens/s 1.00
{"name": "output_throughput", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 212.40807983083667 tokens/s 212.49772251521847 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2.409279035050664 prompts/s 2.401657816872747 prompts/s 1.00
{"name": "input_throughput", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 744.0496134645797 tokens/s 741.6959780587542 tokens/s 1.00
{"name": "output_throughput", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 553.0034231012023 tokens/s 551.2957485475054 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 256,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 14.753997089539254 prompts/s 13.93523069179165 prompts/s 0.94
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 256,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3791.7772520115886 tokens/s 3581.3542877904542 tokens/s 0.94
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 32,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 33.73946767974121 prompts/s 33.83147816882602 prompts/s 1.00
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 32,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1113.40243343146 tokens/s 1116.4387795712585 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2048,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2.048400265133482 prompts/s 1.9463877764005562 prompts/s 0.95
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2048,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4197.172143258505 tokens/s 3988.1485538447396 tokens/s 0.95
{"name": "request_throughput", "description": "VLLM Engine throughput - Dense (with dataset)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"dataset\": \"sharegpt\",\n \"output-len\": 128,\n \"num-prompts\": 1000\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 6.492021825910745 prompts/s 6.192404343785308 prompts/s 0.95
{"name": "token_throughput", "description": "VLLM Engine throughput - Dense (with dataset)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"dataset\": \"sharegpt\",\n \"output-len\": 128,\n \"num-prompts\": 1000\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3035.409724922828 tokens/s 2895.3205749802582 tokens/s 0.95
{"name": "request_throughput", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4.196088612981583 prompts/s 4.083763979594355 prompts/s 0.97
{"name": "input_throughput", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1329.6985205677338 tokens/s 1294.1039674936553 tokens/s 0.97
{"name": "output_throughput", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 959.1335429781043 tokens/s 933.434100343841 tokens/s 0.97
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 64\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 19.016964781417325 prompts/s 18.157041165975567 prompts/s 0.95
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 64\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2472.2054215842522 tokens/s 2360.4153515768235 tokens/s 0.95
{"name": "request_throughput", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2.4020584851036304 prompts/s 2.39572286413871 prompts/s 1.00
{"name": "input_throughput", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 741.8197150929371 tokens/s 739.8631063890773 tokens/s 1.00
{"name": "output_throughput", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 479.953704536233 tokens/s 478.6047366090227 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 0.49191116492745957 prompts/s 0.49191223158841124 prompts/s 1.00
{"name": "input_throughput", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 130.03179733692465 tokens/s 130.03207929808065 tokens/s 1.00
{"name": "output_throughput", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 121.99396890200997 tokens/s 121.98439518929422 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 0.9839505727607054 prompts/s 0.9839856817563846 prompts/s 1.00
{"name": "input_throughput", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 290.12110621373654 tokens/s 290.1314582181425 tokens/s 1.00
{"name": "output_throughput", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 185.76002863149355 tokens/s 185.03850745428812 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 32,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 35.945303611044366 prompts/s 33.94939028407503 prompts/s 0.94
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 32,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1186.1950191644642 tokens/s 1120.329879374476 tokens/s 0.94
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 0.6095226674752755 prompts/s 0.6052346090098714 prompts/s 0.99
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 79.23794677178581 tokens/s 78.68049917128327 tokens/s 0.99
{"name": "request_throughput", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 0.491920434449518 prompts/s 0.4919228246379114 prompts/s 1.00
{"name": "input_throughput", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 130.0342476423856 tokens/s 130.03487946478552 tokens/s 1.00
{"name": "output_throughput", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 120.425401822805 tokens/s 120.68178682567002 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 16\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 10.211156792098073 prompts/s 10.044949283459347 prompts/s 0.98
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 16\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1327.4503829727496 tokens/s 1305.8434068497152 tokens/s 0.98
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 64\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 16.921242610747488 prompts/s 16.029675489773204 prompts/s 0.95
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 64\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2199.7615393971737 tokens/s 2083.857813670517 tokens/s 0.95
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 16\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 6.530512501315939 prompts/s 6.428173522339083 prompts/s 0.98
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 16\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 848.966625171072 tokens/s 835.6625579040808 tokens/s 0.98
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 1024,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3.9797429016837427 prompts/s 3.7695894537815855 prompts/s 0.95
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 1024,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4079.2364742258364 tokens/s 3863.829190126125 tokens/s 0.95
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 512,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 7.840126707917632 prompts/s 7.332134358165357 prompts/s 0.94
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 512,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4021.985001161745 tokens/s 3761.384925738828 tokens/s 0.94
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 32,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 33.498061166616615 prompts/s 33.93942355696572 prompts/s 1.01
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 32,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1105.4360184983484 tokens/s 1120.0009773798688 tokens/s 1.01
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 256,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 14.926884537512484 prompts/s 14.008443757629983 prompts/s 0.94
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 256,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3836.209326140708 tokens/s 3600.1700457109055 tokens/s 0.94
{"name": "request_throughput", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 0.98396092516824 prompts/s 0.9839302024708598 prompts/s 1.00
{"name": "input_throughput", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 290.1241586556061 tokens/s 290.1150999658746 tokens/s 1.00
{"name": "output_throughput", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 212.42732413457134 tokens/s 212.37477466865195 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Engine throughput - Dense (with dataset)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"dataset\": \"sharegpt\",\n \"output-len\": 128,\n \"num-prompts\": 1000\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 6.830945238810128 prompts/s 6.519821599310789 prompts/s 0.95
{"name": "token_throughput", "description": "VLLM Engine throughput - Dense (with dataset)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"dataset\": \"sharegpt\",\n \"output-len\": 128,\n \"num-prompts\": 1000\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3193.8767558580635 tokens/s 3048.4077869737525 tokens/s 0.95
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 64,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 29.62958397815811 prompts/s 29.238407608808572 prompts/s 0.99
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 64,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1925.922958580277 tokens/s 1900.4964945725571 tokens/s 0.99
{"name": "request_throughput", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4.888536218881418 prompts/s 4.709121215429429 prompts/s 0.96
{"name": "input_throughput", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1464.0660826807227 tokens/s 1410.3331431018876 tokens/s 0.96
{"name": "output_throughput", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1111.1463579189437 tokens/s 1070.3534278327447 tokens/s 0.96
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 128,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 18.022109848626442 prompts/s 17.51346855712288 prompts/s 0.97
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 128,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2324.852170472811 tokens/s 2259.2374438688516 tokens/s 0.97
{"name": "request_throughput", "description": "VLLM Engine throughput - 2:4 Sparse (with dataset)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"dataset\": \"sharegpt\",\n \"output-len\": 128,\n \"num-prompts\": 1000,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 6.926850436315806 prompts/s 6.556047214372847 prompts/s 0.95
{"name": "token_throughput", "description": "VLLM Engine throughput - 2:4 Sparse (with dataset)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"dataset\": \"sharegpt\",\n \"output-len\": 128,\n \"num-prompts\": 1000,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3238.718190003818 tokens/s 3065.3454355521685 tokens/s 0.95
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 4\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2.246017530170392 prompts/s 2.2170164864519246 prompts/s 0.99
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 4\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 291.98227892215095 tokens/s 288.21214323875023 tokens/s 0.99
{"name": "request_throughput", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4.506627559289585 prompts/s 4.324349341316379 prompts/s 0.96
{"name": "input_throughput", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1349.6883855224514 tokens/s 1295.097942781062 tokens/s 0.96
{"name": "output_throughput", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1024.294853649879 tokens/s 982.6031619801753 tokens/s 0.96
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 32\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 10.690331125740926 prompts/s 10.388930036120385 prompts/s 0.97
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 32\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1389.7430463463204 tokens/s 1350.5609046956502 tokens/s 0.97
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 1024,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4.16933707496785 prompts/s 3.892330418245492 prompts/s 0.93
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 1024,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4273.570501842046 tokens/s 3989.638678701629 tokens/s 0.93
{"name": "request_throughput", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 0.9839538221767592 prompts/s 0.9839796155979668 prompts/s 1.00
{"name": "input_throughput", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 293.3920708505921 tokens/s 293.39976184694973 tokens/s 1.00
{"name": "output_throughput", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 213.4851809516175 tokens/s 213.50389699244684 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 16,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 31.334556300846025 prompts/s 31.428755959385505 prompts/s 1.00
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 16,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 532.6874571143824 tokens/s 534.2888513095536 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 0.9559154863077745 prompts/s 0.9596519703127205 prompts/s 1.00
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 124.26901322001068 tokens/s 124.75475614065367 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 0.9839527967166866 prompts/s 0.9839558883229262 prompts/s 1.00
{"name": "input_throughput", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 290.1217619545708 tokens/s 290.1226735249759 tokens/s 1.00
{"name": "output_throughput", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 211.02179662651633 tokens/s 209.7793953904479 tokens/s 0.99
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2048,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2.0494001596442346 prompts/s 1.924124501557944 prompts/s 0.94
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2048,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4199.220927111037 tokens/s 3942.531103692227 tokens/s 0.94
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 512,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 7.548544728826626 prompts/s 7.176484972496577 prompts/s 0.95
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 512,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3872.403445888059 tokens/s 3681.536790890744 tokens/s 0.95
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 32,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 30.016098234345332 prompts/s 29.343422148957828 prompts/s 0.98
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 32,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 990.531241733396 tokens/s 968.3329309156082 tokens/s 0.98
{"name": "request_throughput", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4.390861667344669 prompts/s 4.267380272352407 prompts/s 0.97
{"name": "input_throughput", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1391.420153764852 tokens/s 1352.2901345057542 tokens/s 0.97
{"name": "output_throughput", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 880.4380180892837 tokens/s 856.9297875709052 tokens/s 0.97
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 512,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 6.979001990536866 prompts/s 6.701263098899502 prompts/s 0.96
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 512,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3580.228021145412 tokens/s 3437.7479697354443 tokens/s 0.96
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 32,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 31.755163118338366 prompts/s 31.031777748853624 prompts/s 0.98
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 32,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1047.920382905166 tokens/s 1024.0486657121696 tokens/s 0.98
{"name": "request_throughput", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 0.4919499063533326 prompts/s 0.491950897968658 prompts/s 1.00
{"name": "input_throughput", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 133.02981401002583 tokens/s 133.03008215603137 tokens/s 1.00
{"name": "output_throughput", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 124.66338593597683 tokens/s 124.66035754525794 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 1024,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4.125000517694283 prompts/s 3.8786886295230123 prompts/s 0.94
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - 2:4 Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 1024,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"semi_structured_sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4228.12553063664 tokens/s 3975.6558452610875 tokens/s 0.94
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 1024,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4.076586138891234 prompts/s 3.8729066489447503 prompts/s 0.95
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 1024,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4178.500792363515 tokens/s 3969.7293151683693 tokens/s 0.95
{"name": "request_throughput", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4.725148428198028 prompts/s 4.528059485934523 prompts/s 0.96
{"name": "input_throughput", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1415.1331277115514 tokens/s 1356.1070260893682 tokens/s 0.96
{"name": "output_throughput", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1074.029387828364 tokens/s 1029.2098089149733 tokens/s 0.96
{"name": "request_throughput", "description": "VLLM Engine decode throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 4,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2.250250774553635 prompts/s 2.237975060114565 prompts/s 0.99
{"name": "token_throughput", "description": "VLLM Engine decode throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 2,\n \"output-len\": 128,\n \"num-prompts\": 4,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 292.5326006919725 tokens/s 290.93675781489344 tokens/s 0.99
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 512,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 7.664191840452254 prompts/s 7.280564655068441 prompts/s 0.95
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Sparse (synthetic)\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 512,\n \"output-len\": 1,\n \"num-prompts\": 1,\n \"sparsity\": \"sparse_w16a16\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3931.7304141520067 tokens/s 3734.92966805011 tokens/s 0.95
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 16,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 34.47415077884282 prompts/s 34.35765528912806 prompts/s 1.00
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 16,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 586.060563240328 tokens/s 584.080139915177 tokens/s 1.00
{"name": "request_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 512,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 7.910084237445837 prompts/s 7.52226883066602 prompts/s 0.95
{"name": "token_throughput", "description": "VLLM Engine prefill throughput - Dense (synthetic)\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 512,\n \"output-len\": 1,\n \"num-prompts\": 1\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 4057.8732138097143 tokens/s 3858.9239101316684 tokens/s 0.95

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smaller_is_better

Benchmark suite Current: 7ab58f7 Previous: f90ec1c Ratio
{"name": "median_request_latency", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2619.2788065000627 ms 2633.5494479999966 ms 0.99
{"name": "p90_request_latency", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 9985.10877969986 ms 10068.872559999976 ms 0.99
{"name": "p99_request_latency", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 17761.319215569933 ms 17930.13630854987 ms 0.99
{"name": "mean_ttft_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 88.83688074667891 ms 92.6592437199982 ms 0.96
{"name": "median_ttft_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 45.200603000068895 ms 44.195319499976904 ms 1.02
{"name": "p90_ttft_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 201.91823580000798 ms 210.72332220009002 ms 0.96
{"name": "p99_ttft_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 345.1549884900575 ms 363.0999396899866 ms 0.95
{"name": "mean_tpot_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 14.4894962146852 ms 14.686820727573314 ms 0.99
{"name": "median_tpot_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 14.596964296206833 ms 14.84155859682859 ms 0.98
{"name": "p90_tpot_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 16.367209120072495 ms 16.71862453072956 ms 0.98
{"name": "p99_tpot_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 19.66200627144196 ms 20.001186579111977 ms 0.98
{"name": "median_request_latency", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 191071.20936200046 ms 206087.0038635003 ms 0.93
{"name": "p90_request_latency", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 339083.8620649989 ms 366551.0936865003 ms 0.93
{"name": "p99_request_latency", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 406316.94923098956 ms 435705.4449421206 ms 0.93
{"name": "mean_ttft_ms", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 137350.5730485483 ms 151123.96824455468 ms 0.91
{"name": "median_ttft_ms", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 135007.71913050086 ms 149038.3484845006 ms 0.91
{"name": "p90_ttft_ms", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 276942.3168759004 ms 303024.81096159935 ms 0.91
{"name": "p99_ttft_ms", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 310185.3205451214 ms 338680.9228697209 ms 0.92
{"name": "mean_tpot_ms", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 261.5560679996473 ms 276.70666837276286 ms 0.95
{"name": "median_tpot_ms", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 244.50101613202872 ms 255.73205134062204 ms 0.96
{"name": "p90_tpot_ms", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 280.7126784166444 ms 292.64992902503434 ms 0.96
{"name": "p99_tpot_ms", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 994.7104334228401 ms 1136.798770819434 ms 0.88
{"name": "median_request_latency", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 12437.860401999842 ms 16036.010215999795 ms 0.78
{"name": "p90_request_latency", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 54948.15043390064 ms 71744.16097620002 ms 0.77
{"name": "p99_request_latency", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 107360.20512129967 ms 142352.26692373006 ms 0.75
{"name": "mean_ttft_ms", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 193.7252187400045 ms 220.36655344799874 ms 0.88
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{"name": "median_ttft_ms", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 70.48189799934335 ms 74.13111950063467 ms 0.95
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{"name": "mean_tpot_ms", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 12.46868503530727 ms 12.501530566054361 ms 1.00
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{"name": "p90_tpot_ms", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 17.01648075791713 ms 16.530619358048135 ms 1.03
{"name": "p99_tpot_ms", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 29.542964121036466 ms 30.16093324647077 ms 0.98
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{"name": "p99_request_latency", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 403023.3420420707 ms 429512.8041773001 ms 0.94
{"name": "mean_ttft_ms", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 136576.43001856565 ms 148768.94288126435 ms 0.92
{"name": "median_ttft_ms", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 136384.48763699943 ms 148556.2602619998 ms 0.92
{"name": "p90_ttft_ms", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 273587.05745109974 ms 297024.6507920003 ms 0.92
{"name": "p99_ttft_ms", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 306551.3317420394 ms 331554.0625582898 ms 0.92
{"name": "mean_tpot_ms", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 239.99644394620634 ms 253.9808382365661 ms 0.94
{"name": "median_tpot_ms", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 242.32272250917546 ms 252.70005300059682 ms 0.96
{"name": "p90_tpot_ms", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 267.832103347204 ms 282.3308798349177 ms 0.95
{"name": "p99_tpot_ms", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 525.5693571896837 ms 630.5546354305361 ms 0.83
{"name": "median_request_latency", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 23436.39784449897 ms 29888.196538001466 ms 0.78
{"name": "p90_request_latency", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 105979.07188330116 ms 120327.39291680002 ms 0.88
{"name": "p99_request_latency", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 201917.7512382004 ms 227289.1390777593 ms 0.89
{"name": "mean_ttft_ms", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 339.37380958332386 ms 3017.135163384695 ms 0.11
{"name": "median_ttft_ms", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 238.49984600019525 ms 391.10383150000416 ms 0.61
{"name": "p90_ttft_ms", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 687.8398275997827 ms 9661.945217599898 ms 0.07119061556536618
{"name": "p99_ttft_ms", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1628.6544391597452 ms 11902.70134517963 ms 0.14
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{"name": "median_tpot_ms", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 17.32497385170151 ms 17.391109768012377 ms 1.00
{"name": "p90_tpot_ms", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 30.29504214289253 ms 30.609102290474677 ms 0.99
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{"name": "mean_tpot_ms", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 30.371336993030603 ms 32.39315969992204 ms 0.94
{"name": "median_tpot_ms", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 29.232299756898318 ms 30.691877819661574 ms 0.95
{"name": "p90_tpot_ms", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 39.3796813749782 ms 42.654225678777024 ms 0.92
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{"name": "median_request_latency", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2314.385872999992 ms 2424.9027700002443 ms 0.95
{"name": "p90_request_latency", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 9605.507370899528 ms 9938.114032800242 ms 0.97
{"name": "p99_request_latency", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 17769.69579761003 ms 18299.568632519822 ms 0.97
{"name": "mean_ttft_ms", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 117.91140901331528 ms 125.07054965599428 ms 0.94
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{"name": "p99_ttft_ms", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 331.8509067498596 ms 353.13250212996513 ms 0.94
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{"name": "p99_tpot_ms", "description": "VLLM Serving - Dense\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-marlin\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 12.41987089233612 ms 12.406804291732 ms 1.00
{"name": "median_request_latency", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2478.4277730000213 ms 2515.1734594999198 ms 0.99
{"name": "p90_request_latency", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 8979.482846999896 ms 9478.638828799902 ms 0.95
{"name": "p99_request_latency", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 17972.594065469948 ms 17916.419126929984 ms 1.00
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{"name": "median_ttft_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 64.61351349992128 ms 67.3158519999788 ms 0.96
{"name": "p90_ttft_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 223.17261599989706 ms 240.7319551999081 ms 0.93
{"name": "p99_ttft_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 369.0545601300023 ms 392.60241530994057 ms 0.94
{"name": "mean_tpot_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 17.00279779362755 ms 17.224175412077546 ms 0.99
{"name": "median_tpot_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 16.27501612851011 ms 16.43353957424866 ms 0.99
{"name": "p90_tpot_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 20.289086788996396 ms 20.76168343563268 ms 0.98
{"name": "p99_tpot_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 36.030136238974656 ms 37.352690176005694 ms 0.96
{"name": "median_request_latency", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 3823.430648999988 ms 4070.5437429999165 ms 0.94
{"name": "p90_request_latency", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 16461.25935949995 ms 17407.078864799973 ms 0.95
{"name": "p99_request_latency", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 28763.213804109986 ms 30302.0763944201 ms 0.95
{"name": "mean_ttft_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 128.6937332066715 ms 136.37600092666406 ms 0.94
{"name": "median_ttft_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 96.25588549988606 ms 102.05976500003544 ms 0.94
{"name": "p90_ttft_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 295.37767780000195 ms 304.77485379994965 ms 0.97
{"name": "p99_ttft_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 480.1794475699716 ms 520.1094485100973 ms 0.92
{"name": "mean_tpot_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 29.00333794308105 ms 30.73214922713832 ms 0.94
{"name": "median_tpot_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 26.999675672183546 ms 28.051313986612502 ms 0.96
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{"name": "median_ttft_ms", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 209.3643259995588 ms 369.55214499994327 ms 0.57
{"name": "p90_ttft_ms", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 493.7132595008739 ms 4845.089579200432 ms 0.10
{"name": "p99_ttft_ms", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 816.04874819026 ms 6041.424469978483 ms 0.14
{"name": "mean_tpot_ms", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 179.34730313687857 ms 202.69628210870007 ms 0.88
{"name": "median_tpot_ms", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 184.05335414619367 ms 212.97724416554433 ms 0.86
{"name": "p90_tpot_ms", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 241.7566609295632 ms 269.47397744254056 ms 0.90
{"name": "p99_tpot_ms", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 314.7274433692578 ms 341.11945666913056 ms 0.92
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{"name": "p99_request_latency", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 29940.81838422985 ms 32017.54494271006 ms 0.94
{"name": "mean_ttft_ms", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 126.88884918402863 ms 134.5176232626351 ms 0.94
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{"name": "p99_ttft_ms", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 450.49049153032684 ms 464.1880664990276 ms 0.97
{"name": "mean_tpot_ms", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 37.29437532613624 ms 39.725315734985735 ms 0.94
{"name": "median_tpot_ms", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 31.758328713117006 ms 34.42999926185959 ms 0.92
{"name": "p90_tpot_ms", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 57.45083083182346 ms 61.514389520161785 ms 0.93
{"name": "p99_tpot_ms", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"750,2.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 103.80553039372755 ms 109.86417063065396 ms 0.94
{"name": "median_request_latency", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 1661.0156964998168 ms 1657.9717610002263 ms 1.00
{"name": "p90_request_latency", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 6555.79947819997 ms 6569.333387600363 ms 1.00
{"name": "p99_request_latency", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 11987.341231040105 ms 12025.861700070052 ms 1.00
{"name": "mean_ttft_ms", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 90.79138414669312 ms 94.51856139336694 ms 0.96
{"name": "median_ttft_ms", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 50.8824309999909 ms 51.128068000252824 ms 1.00
{"name": "p90_ttft_ms", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 197.39277479984588 ms 211.64880940023062 ms 0.93
{"name": "p99_ttft_ms", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 349.61140690053946 ms 367.9637827699477 ms 0.95
{"name": "mean_tpot_ms", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 9.551353622154886 ms 9.573305263580215 ms 1.00
{"name": "median_tpot_ms", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 9.503634815360039 ms 9.476364134911423 ms 1.00
{"name": "p90_tpot_ms", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 11.05627382566107 ms 10.906913883190983 ms 1.01
{"name": "p99_tpot_ms", "description": "VLLM Serving - Dense\nmodel - TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 13.908910758781355 ms 14.066048566718507 ms 0.99
{"name": "median_request_latency", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 2668.308303500453 ms 2730.8756865004398 ms 0.98
{"name": "p90_request_latency", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 9529.234044699664 ms 9896.515330199694 ms 0.96
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{"name": "median_tpot_ms", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 14.144933609625358 ms 14.361914611512093 ms 0.98
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{"name": "p99_tpot_ms", "description": "VLLM Serving - Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned50\nmax-model-len - 4096\nsparsity - sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"300,1\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 35.9319615621996 ms 36.801621956764755 ms 0.98
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{"name": "p99_ttft_ms", "description": "VLLM Serving - 2:4 Sparse\nmodel - neuralmagic/OpenHermes-2.5-Mistral-7B-pruned2.4\nmax-model-len - 4096\nsparsity - semi_structured_sparse_w16a16\nbenchmark_serving {\n \"nr-qps-pair_\": \"1500,5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 664.6819873395542 ms 783.1067651508598 ms 0.85
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{"name": "median_tpot_ms", "description": "VLLM Serving - Dense\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"150,0.5\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 13.69640661887533 ms 13.792765900180761 ms 0.99
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{"name": "mean_ttft_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 116664.41967879332 ms 128320.23090140166 ms 0.91
{"name": "median_ttft_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 114155.78997700004 ms 126059.8570694999 ms 0.91
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{"name": "median_tpot_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 227.3823853200992 ms 237.16568343332938 ms 0.96
{"name": "p90_tpot_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 258.384261493575 ms 272.3127474702717 ms 0.95
{"name": "p99_tpot_ms", "description": "VLLM Serving - Dense\nmodel - teknium/OpenHermes-2.5-Mistral-7B\nmax-model-len - 4096\nsparsity - None\nbenchmark_serving {\n \"nr-qps-pair_\": \"3000,10\",\n \"dataset\": \"sharegpt\"\n}", "gpu_description": "NVIDIA A10G x 4", "vllm_version": "0.1.0", "python_version": "3.10.12 (main, Mar 7 2024, 18:39:53) [GCC 9.4.0]", "torch_version": "2.1.2+cu121"} 653.623193519797 ms 930.097252701919 ms 0.70

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