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@leejet leejet commented Oct 10, 2025

Qwen Image Edit

.\bin\Release\sd.exe --diffusion-model  ..\..\ComfyUI\models\diffusion_models\Qwen_Image_Edit-Q8_0.gguf --vae ..\..\ComfyUI\models\vae\qwen_image_vae.safetensors  --qwen2vl ..\..\ComfyUI\models\text_encoders\qwen_2.5_vl_7b.safetensors --cfg-scale 2.5 --sampling-method euler -v --offload-to-cpu --diffusion-fa --flow-shift 3 -r ..\assets\flux\flux1-dev-q8_0.png -p "change 'flux.cpp' to 'edit.cpp'" --seed 1118877715456453
qwen_image_edit

Qwen Image Edit 2509

.\bin\Release\sd.exe --diffusion-model  ..\..\ComfyUI\models\diffusion_models\Qwen-Image-Edit-2509-Q8_0.gguf --vae ..\..\ComfyUI\models\vae\qwen_image_vae.safetensors  --qwen2vl ..\..\ComfyUI\models\text_encoders\qwen_2.5_vl_7b.safetensors --cfg-scale 2.5 --sampling-method euler -v --offload-to-cpu --diffusion-fa --flow-shift 3 -r .\qwen-pose2.png -r .\replicate-prediction-2rq8q6nrg5rmc0csex6818jzk8.jpeg -p "The woman in image 2 adopts the pose from image 1" -H 1024 -W 1024

image 1:

image 2:

result:
qwen_image_edit_multi

@leejet leejet mentioned this pull request Oct 10, 2025
@LostRuins
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LostRuins commented Oct 11, 2025

Seems to work fine on vulkan.

Edit: Running multiple generations on the same instance causes issues.
I get conditioner.hpp:1558: GGML_ASSERT(hidden_states->ne[1] > prompt_template_encode_start_idx)
I think this can be fixed by resetting prompt_template_encode_start_idx back to 34.

The quality is... weird. It seems a lot less coherent than the reference implementation. For simple tasks like background removal it's fine, but anything else seems off. Are we supposed to ensure the input reference image and output image is exactly the same size?

@leejet
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leejet commented Oct 11, 2025

I get conditioner.hpp:1558: GGML_ASSERT(hidden_states->ne[1] > prompt_template_encode_start_idx)
I think this can be fixed by resetting prompt_template_encode_start_idx back to 34.

@LostRuins The Qwen image edit model uses a different system prompt, so it requires a different prompt_template_encode_start_idx. Can you share the detailed output? In theory, this issue shouldn’t be triggered.

The quality is... weird. It seems a lot less coherent than the reference implementation. For simple tasks like background removal it's fine, but anything else seems off.

Can you give an example?

Are we supposed to ensure the input reference image and output image is exactly the same size?

That’s not necessary — the Qwen image edit pipeline will automatically resize the reference image to an appropriate size.

@LostRuins
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In theory, this issue shouldn’t be triggered.

It will not be triggered in CLI, but in server mode it can be, because you initialize the Conditioner once on model load

struct Qwen2_5_VLCLIPEmbedder : public Conditioner {
    Qwen::Qwen2Tokenizer tokenizer;
    std::shared_ptr<Qwen::Qwen2_5_VLRunner> qwenvl;
    int prompt_template_encode_start_idx = 34;

later you overwrite it, but never reset it back if it is reused without a ref image later

    SDCondition get_learned_condition(ggml_context* work_ctx,
                                      int n_threads,
                                      const ConditionerParams& conditioner_params) {
        std::string prompt;
        std::vector<std::pair<int, ggml_tensor*>> image_embeds;
        size_t system_prompt_length = 0;
        if (qwenvl->enable_vision && conditioner_params.ref_images.size() > 0) {
            LOG_INFO("QwenImageEditPlusPipeline");
            prompt_template_encode_start_idx = 64;                            //this is permanent!!

this is a simple fix:

    SDCondition get_learned_condition(ggml_context* work_ctx,
                                      int n_threads,
                                      const ConditionerParams& conditioner_params) {
        std::string prompt;
        std::vector<std::pair<int, ggml_tensor*>> image_embeds;
        size_t system_prompt_length = 0;
        prompt_template_encode_start_idx = 34;                //reset it back in case the user removes their reference images.
        if (qwenvl->enable_vision && conditioner_params.ref_images.size() > 0) {
            LOG_INFO("QwenImageEditPlusPipeline");
            prompt_template_encode_start_idx = 64;

Can you give an example?

Sure, the below was done with 20 steps on Qwen_Image_Edit-Q4_K_S.gguf

Prompt 1: Remove the background
s1
Result 1:
r1

Prompt 2: Change the hair color to blue and add a cat
s2

Result 2:
r2

In each case I seem to be losing a bunch of quality and detail compared to the source. It's hard to explain exactly what I mean but hopefully the pictures make sense.

@leejet
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leejet commented Oct 11, 2025

The result of q8_0 looks good.

Prompt 1: Remove the background

p1

Prompt 2: Change the hair color to blue and add a cat

p2

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leejet commented Oct 12, 2025

The results of q4_k_s also look good now.

 .\bin\Release\sd.exe --diffusion-model  ..\..\ComfyUI\models\diffusion_models\Qwen-Image-Edit-2509-Q4_K_S.gguf --vae ..\..\ComfyUI\models\vae\qwen_image_vae.safetensors  --qwen2vl ..\..\ComfyUI\models\text_encoders\Qwen2.5-VL-7B-Instruct-Q8_0.gguf --qwen2vl_vision ..\..\ComfyUI\models\text_encoders\Qwen2.5-VL-7B-Instruct.mmproj-Q8_0.gguf --cfg-scale 2.5 --sampling-method euler -v --offload-to-cpu --diffusion-fa --flow-shift 3 -r girl.png -p "Remove the background"
output

@wbruna
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wbruna commented Oct 12, 2025

Just confirming the Pruning models work fine with this branch. I only noticed very small image changes between this branch and the qwen_edit + Pruning PR.

@LostRuins
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Just a matter of curiosity @leejet , how did you arrive at a value of 1/128.f for the precision fix scaler for qwen (and also why is it 1/32 for the t5 and to_add_out)?

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leejet commented Oct 12, 2025

Just a matter of curiosity @leejet , how did you arrive at a value of 1/128.f for the precision fix scaler for qwen (and also why is it 1/32 for the t5 and to_add_out)?

The scaling value was determined through testing. I tested with different prompts and tried to keep the scaling value as small as possible while ensuring the issue was fixed.

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LostRuins commented Oct 12, 2025

image

much better now!

The quality has improved a lot after the fixes

@leejet leejet changed the base branch from qwen_image to master October 12, 2025 16:06
@leejet leejet merged commit 2e9242e into master Oct 13, 2025
8 checks passed
stduhpf added a commit to stduhpf/stable-diffusion.cpp that referenced this pull request Oct 23, 2025
* docs: add sd.cpp-webui as an available frontend (leejet#738)

* fix: correct head dim check and L_k padding of flash attention (leejet#736)

* fix: convert f64 to f32 and i64 to i32 when loading weights

* docs: add LocalAI to README's UIs (leejet#741)

* sync: update ggml

* sync: update ggml

* feat: upgrade musa sdk to rc4.2.0 (leejet#732)

* feat: change image dimensions requirement for DiT models (leejet#742)

* feat: add missing models and parameters to image metadata (leejet#743)

* feat: add new scheduler types, clip skip and vae to image embedded params

- If a non default scheduler is set, include it in the 'Sampler' tag in the data
embedded into the final image.
- If a custom VAE path is set, include the vae name (without path and extension)
in embedded image params under a `VAE:` tag.
- If a custom Clip skip is set, include that Clip skip value in embedded image
params under a `Clip skip:` tag.

* feat: add separate diffusion and text models to metadata

---------

Co-authored-by: one-lithe-rune <skapusniak@lithe-runes.com>

* refector: optimize the usage of tensor_types

* feat: support build against system installed GGML library (leejet#749)

* chore: avoid setting GGML_MAX_NAME when building against external ggml (leejet#751)

An external ggml will most likely have been built with the default
GGML_MAX_NAME value (64), which would be inconsistent with the value
set by our build (128). That would be an ODR violation, and it could
easily cause memory corruption issues due to the different
sizeof(struct ggml_tensor) values.

For now, when linking against an external ggml, we demand it has been
patched with a bigger GGML_MAX_NAME, since we can't check against a
value defined only at build time.

* Conv2D direct support (leejet#744)

* Conv2DDirect for VAE stage

* Enable only for Vulkan, reduced duplicated code

* Cmake option to use conv2d direct

* conv2d direct always on for opencl

* conv direct as a flag

* fix merge typo

* Align conv2d behavior to flash attention's

* fix readme

* add conv2d direct for controlnet

* add conv2d direct for esrgan

* clean code, use enable_conv2d_direct/get_all_blocks

* format code

---------

Co-authored-by: leejet <leejet714@gmail.com>

* sync: update ggml, make cuda im2col a little faster

* chore: add Nvidia 30 series (cuda arch 86) to build

* feat: throttle model loading progress updates (leejet#782)

Some terminals have slow display latency, so frequent output
during model loading can actually slow down the process.

Also, since tensor loading times can vary a lot, the progress
display now shows the average across past iterations instead
of just the last one.

* docs: add missing dash to docs/chroma.md (leejet#771)

* docs: add compile option needed by Ninja (leejet#770)

* feat: show usage on unknown arg (leejet#767)

* fix: typo in the verbose long flag (leejet#783)

* feat: add wan2.1/2.2 support (leejet#778)

* add wan vae suppport

* add wan model support

* add umt5 support

* add wan2.1 t2i support

* make flash attn work with wan

* make wan a little faster

* add wan2.1 t2v support

* add wan gguf support

* add offload params to cpu support

* add wan2.1 i2v support

* crop image before resize

* set default fps to 16

* add diff lora support

* fix wan2.1 i2v

* introduce sd_sample_params_t

* add wan2.2 t2v support

* add wan2.2 14B i2v support

* add wan2.2 ti2v support

* add high noise lora support

* sync: update ggml submodule url

* avoid build failure on linux

* avoid build failure

* update ggml

* update ggml

* fix sd_version_is_wan

* update ggml, fix cpu im2col_3d

* fix ggml_nn_attention_ext mask

* add cache support to ggml runner

* fix the issue of illegal memory access

* unify image loading processing

* add wan2.1/2.2 FLF2V support

* fix end_image mask

* update to latest ggml

* add GGUFReader

* update docs

* feat: add support for timestep boundary based automatic expert routing in Wan MoE (leejet#779)

* Wan MoE: Automatic expert routing based on timestep boundary

* unify code style and fix some issues

---------

Co-authored-by: leejet <leejet714@gmail.com>

* feat: add flow shift parameter (for SD3 and Wan) (leejet#780)

* Add flow shift parameter (for SD3 and Wan)

* unify code style and fix some issues

---------

Co-authored-by: leejet <leejet714@gmail.com>

* docs: update docs and help message

* chore: update to c++17

* docs: update docs/wan.md

* fix: add flash attn support check (leejet#803)

* feat: support incrementing ref image index (omni-kontext) (leejet#755)

* kontext: support  ref images indices

* lora: support x_embedder

* update help message

* Support for negative indices

* support for OmniControl (offsets at index 0)

* c++11 compat

* add --increase-ref-index option

* simplify the logic and fix some issues

* update README.md

* remove unused variable

---------

Co-authored-by: leejet <leejet714@gmail.com>

* feat: add detailed tensor loading time stat (leejet#793)

* fix: clarify lora quant support and small fixes (leejet#792)

* fix: accept NULL in sd_img_gen_params_t::input_id_images_path (leejet#809)

* chore: update flash attention warnings (leejet#805)

* fix: use {} for params init instead of memset (leejet#781)

* chore: remove sd3 flash attention warn (leejet#812)

* feat: use log_printf to print ggml logs (leejet#545)

* chore: add install() support in CMakeLists.txt (leejet#540)

* feat: add SmoothStep Scheduler (leejet#813)

* feat: add sd3 flash attn support (leejet#815)

* fix: make tiled VAE reuse the compute buffer (leejet#821)

* feat: reduce CLIP memory usage with no embeddings (leejet#768)

* fix: make weight override more robust against ggml changes (leejet#760)

* fix: do not force VAE type to f32 on SDXL (leejet#716)

This seems to be a leftover from the initial SDXL support: it's
not enough to avoid NaN issues, and it's not not needed for the
fixed sdxl-vae-fp16-fix .

* feat: use Euler sampling by default for SD3 and Flux (leejet#753)

Thank you for your contribution.

* fix: harden for large files (leejet#643)

* feat: Add SYCL Dockerfile (leejet#651)

* feat: increase work_ctx memory buffer size (leejet#814)

* docs: update docs

* feat: add VAE encoding tiling support and adaptive overlap  (leejet#484)

* implement  tiling vae encode support

* Tiling (vae/upscale): adaptative overlap

* Tiling: fix edge case

* Tiling: fix crash when less than 2 tiles per dim

* remove extra dot

* Tiling: fix edge cases for adaptative overlap

* tiling: fix edge case

* set vae tile size via env var

* vae tiling: refactor again, base on smaller buffer for alignment

* Use bigger tiles for encode (to match compute buffer size)

* Fix edge case when tile is bigger than latent

* non-square VAE tiling (#3)

* refactor tile number calculation

* support non-square tiles

* add env var to change tile overlap

* add safeguards and better error messages for SD_TILE_OVERLAP

* add safeguards and include overlapping factor for SD_TILE_SIZE

* avoid rounding issues when specifying SD_TILE_SIZE as a factor

* lower SD_TILE_OVERLAP limit

* zero-init empty output buffer

* Fix decode latent size

* fix encode

* tile size params instead of env

* Tiled vae parameter validation (#6)

* avoid crash with invalid tile sizes, use 0 for default

* refactor default tile size, limit overlap factor

* remove explicit parameter for relative tile size

* limit encoding tile to latent size

* unify code style and format code

* update docs

* fix get_tile_sizes in decode_first_stage

---------

Co-authored-by: Wagner Bruna <wbruna@users.noreply.github.com>
Co-authored-by: leejet <leejet714@gmail.com>

* feat: add vace support (leejet#819)

* add wan vace t2v support

* add --vace-strength option

* add vace i2v support

* fix the processing of vace_context

* add vace v2v support

* update docs

* feat: optimize tensor loading time (leejet#790)

* opt tensor loading

* fix build failure

* revert the changes

* allow the use of n_threads

* fix lora loading

* optimize lora loading

* add mutex

* use atomic

* fix build

* fix potential duplicate issue

* avoid duplicate lookup of lora tensor

* fix progeress bar

* remove unused remove_duplicates

---------

Co-authored-by: leejet <leejet714@gmail.com>

* refactor: simplify the logic of pm id image loading (leejet#827)

* feat: add sgm_uniform scheduler, simple scheduler, and support for NitroFusion (leejet#675)

* feat: Add timestep shift and two new schedulers

* update readme

* fix spaces

* format code

* simplify SGMUniformSchedule

* simplify shifted_timestep logic

* avoid conflict

---------

Co-authored-by: leejet <leejet714@gmail.com>

* refactor: move tiling cacl and debug print into the tiling code branch (leejet#833)

* refactor: simplify DPM++ (2S) Ancestral (leejet#667)

* chore: set release tag by commit count

* chore: fix workflow (leejet#836)

* fix: avoid multithreading issues in the model loader

* fix: avoid segfault for pix2pix models without reference images (leejet#766)

* fix: avoid segfault for pix2pix models with no reference images

* fix: default to empty reference on pix2pix models to avoid segfault

* use resize instead of reserve

* format code

---------

Co-authored-by: leejet <leejet714@gmail.com>

* refactor: remove unused --normalize-input parameter (leejet#835)

* fix: correct tensor deduplication logic (leejet#844)

* docs: include Vulkan compatibility for LoRA quants (leejet#845)

* docs: HipBLAS / ROCm build instruction fix (leejet#843)

* fix: tensor loading thread count (leejet#854)

* fix: optimize the handling of CLIP embedding weight (leejet#840)

* sync: update ggml

* sync: update ggml

* fix: optimize the handling of embedding weight (leejet#859)

* feat: add support for Flux Controls and Flex.2 (leejet#692)

* docs: update README.md (leejet#866)

* chore: fix dockerfile libgomp1 dependency + improvements (leejet#852)

* fix: ensure directory iteration results are sorted by filename (leejet#858)

* chore: fix vulkan ci (leejet#878)

* feat: add support for more esrgan models & x2 & x1 models (leejet#855)

* feat: add a stand-alone upscale mode (leejet#865)

* feat: add a stand-alone upscale mode

* fix prompt option check

* format code

* update README.md

---------

Co-authored-by: leejet <leejet714@gmail.com>

* refactor: deal with default img-cfg-scale at the library level (leejet#869)

* feat: add Qwen Image support (leejet#851)

* add qwen tokenizer

* add qwen2.5 vl support

* mv qwen.hpp -> qwenvl.hpp

* add qwen image model

* add qwen image t2i pipeline

* fix qwen image flash attn

* add qwen image i2i pipline

* change encoding of vocab_qwen.hpp to utf8

* fix get_first_stage_encoding

* apply jeffbolz f32 patch

leejet#851 (comment)

* fix the issue that occurs when using CUDA with k-quants weights

* optimize the handling of the FeedForward precision fix

* to_add_out precision fix

* update docs

* fix: resolve VAE tiling problem in Qwen Image (leejet#873)

* fix: avoid generating black images when running T5 on the GPU (leejet#882)

* fix: correct canny preprocessor (leejet#861)

* fix: better progress display for second-order samplers (leejet#834)

* feat: add Qwen Image Edit support (leejet#877)

* add ref latent support for qwen image

* optimize clip_preprocess and fix get_first_stage_encoding

* add qwen2vl vit support

* add qwen image edit support

* fix qwen image edit pipeline

* add mmproj file support

* support dynamic number of Qwen image transformer blocks

* set prompt_template_encode_start_idx every time

* to_add_out precision fix

* to_out.0 precision fix

* update docs

---------

Co-authored-by: Daniele <57776841+daniandtheweb@users.noreply.github.com>
Co-authored-by: Erik Scholz <Green-Sky@users.noreply.github.com>
Co-authored-by: leejet <leejet714@gmail.com>
Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
Co-authored-by: R0CKSTAR <xiaodong.ye@mthreads.com>
Co-authored-by: stduhpf <stephduh@live.fr>
Co-authored-by: one-lithe-rune <skapusniak@lithe-runes.com>
Co-authored-by: Seas0 <seashkey@gmail.com>
Co-authored-by: NekopenDev <197017459+nekopendev@users.noreply.github.com>
Co-authored-by: SmallAndSoft <45131567+SmallAndSoft@users.noreply.github.com>
Co-authored-by: Markus Hartung <mail@hartmark.se>
Co-authored-by: clibdev <52199778+clibdev@users.noreply.github.com>
Co-authored-by: Richard Palethorpe <io@richiejp.com>
Co-authored-by: rmatif <kingrealriadh@gmail.com>
Co-authored-by: vmobilis <75476228+vmobilis@users.noreply.github.com>
Co-authored-by: Stefan-Olt <stefan-oltmanns@gmx.net>
Co-authored-by: Sharuzzaman Ahmat Raslan <sharuzzaman@gmail.com>
Co-authored-by: Serkan Sahin <14278530+SergeantSerk@users.noreply.github.com>
Co-authored-by: Pedrito <pedro.c.vfx@gmail.com>
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4 participants