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Update iphone 15 pro benchmarking numbers #2927

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Update iphone 15 pro benchmarking numbers #2927

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15 changes: 9 additions & 6 deletions examples/models/llama2/README.md
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Expand Up @@ -32,15 +32,19 @@ Note that groupsize less than 128 was not enabled, since such model were still t

## Performance

Performance was measured on Samsung Galaxy S22, S23, S24 and One Plus 12. Measurement performance is in terms of tokens/second.
Performance was measured on Samsung Galaxy S22, S24, One Plus 12 and iPhone 15 max Pro. Measurement performance is in terms of tokens/second.

|Device | Groupwise 4-bit (128) | Groupwise 4-bit (256)
|--------| ---------------------- | ---------------
|Galaxy S22 | 8.15 tokens/second | 8.3 tokens/second |
|Galaxy S24 | 10.66 tokens/second | 11.26 tokens/second |
|One plus 12 | 11.55 tokens/second | 11.6 tokens/second |
|iPhone 15 pro | x | x |
|Galaxy S22* | 8.15 tokens/second | 8.3 tokens/second |
|Galaxy S24* | 10.66 tokens/second | 11.26 tokens/second |
|One plus 12* | 11.55 tokens/second | 11.6 tokens/second |
|Galaxy S22** | 5.5 tokens/second | 5.9 tokens/second |
|iPhone 15 pro** | ~6 tokens/second | ~6 tokens/second |

*: Measured via adb binary based [workflow](#step-5-run-benchmark-on)

**: Measured via app based [workflow](#step-6-build-mobile-apps)

# Instructions

Expand Down Expand Up @@ -241,7 +245,6 @@ Please refer to [this tutorial](https://pytorch.org/executorch/main/llm/llama-de
- Enabling LLama2 7b and other architectures via Vulkan
- Enabling performant execution of widely used quantization schemes.

TODO

# Notes
This example tries to reuse the Python code, with minimal modifications to make it compatible with current ExecuTorch:
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