Qwen-Image-Edit-2511作為一款性能出色的圖像編輯模型，在ComfyUI中部署時卻受限於顯存資源。本文針對4090顯卡（24G顯存）場景，分享量化模型的部署流程、關鍵避坑點，以及不同採樣步數下的效果對比，幫助大家快速落地實踐。
一、前置準備：ComfyUI安裝
ComfyUI基礎安裝流程此處不贅述，推薦參考官方中文指南，步驟清晰且適配Linux環境：ComfyUI Linux安裝官方指南
二、核心問題：顯存限制與解決方案
4090顯卡的24G顯存無法承載Qwen-Image-Edit-2511原始模型（顯存溢出），因此必須使用量化模型。考慮到外網訪問和下載限制，本文提供基於hugging-face鏡像和modelscope的國內可訪問下載鏈接，同時明確各模型的存放路徑（直接關係到模型能否正常加載）。
2.1 量化模型下載清單（含路徑+命令）
所有模型需下載至ComfyUI對應目錄，以下是完整的路徑説明和wget下載命令（複製到終端直接執行即可）：
1. LoRA模型（路徑：ComfyUI/models/loras）
wget https://hf-mirror.com/lightx2v/Qwen-Image-Edit-2511-Lightning/resolve/main/Qwen-Image-Edit-2511-Lightning-4steps-V1.0-bf16.safetensors2. VAE模型（路徑：ComfyUI/models/vae）
wget https://hf-mirror.com/Comfy-Org/Qwen-Image_ComfyUI/resolve/main/split_files/vae/qwen_image_vae.safetensors3. UNet模型（路徑：ComfyUI/models/unet）
wget "https://modelscope.cn/api/v1/models/unsloth/Qwen-Image-Edit-2511-GGUF/repo?Revision=master&FilePath=qwen-image-edit-2511-Q4_K_M.gguf" -O qwen-image-edit-2511-Q4_K_M.gguf4. CLIP模型（路徑：ComfyUI/models/clip）
# 主模型文件
wget -c "https://modelscope.cn/api/v1/models/unsloth/Qwen2.5-VL-7B-Instruct-GGUF/repo?Revision=master&FilePath=Qwen2.5-VL-7B-Instruct-Q4_K_M.gguf" -O Qwen2.5-VL-7B-Instruct-Q4_K_M.gguf
# 關鍵依賴文件（必下！）
wget -c "https://modelscope.cn/api/v1/models/unsloth/Qwen2.5-VL-7B-Instruct-GGUF/repo?Revision=master&FilePath=mmproj-F16.gguf" -O Qwen2.5-VL-7B-Instruct-mmproj-BF16.gguf2.2 致命坑點：缺失mmproj文件導致的報錯解決方案
⚠️ 重點提醒：CLIP模型對應的mmproj文件是必下載項！缺失該文件會直接導致圖像編輯時出現「矩陣維度不匹配」的致命錯誤，排查過程耗時耗力。
我首次部署時因遺漏該文件，出現如下報錯（核心信息：mat1 and mat2 shapes cannot be multiplied）：
Prompt executed in 10.11 seconds
got prompt
!!! Exception during processing !!! mat1 and mat2 shapes cannot be multiplied (748x1280 and 3840x1280)
Traceback (most recent call last):
File "/root/comfy/ComfyUI/execution.py", line 516, in execute
output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy/ComfyUI/execution.py", line 330, in get_output_data
return_values = await _async_map_node_over_list(prompt_id, unique_id, obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy/ComfyUI/execution.py", line 304, in _async_map_node_over_list
await process_inputs(input_dict, i)
File "/root/comfy/ComfyUI/execution.py", line 292, in process_inputs
result = f(**inputs)
^^^^^^^^^^^
File "/root/comfy/ComfyUI/comfy_api/internal/__init__.py", line 149, in wrapped_func
return method(locked_class, **inputs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy/ComfyUI/comfy_api/latest/_io.py", line 1520, in EXECUTE_NORMALIZED
to_return = cls.execute(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy/ComfyUI/comfy_extras/nodes_qwen.py", line 103, in execute
conditioning = clip.encode_from_tokens_scheduled(tokens)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy/ComfyUI/comfy/sd.py", line 207, in encode_from_tokens_scheduled
pooled_dict = self.encode_from_tokens(tokens, return_pooled=return_pooled, return_dict=True)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy/ComfyUI/comfy/sd.py", line 271, in encode_from_tokens
o = self.cond_stage_model.encode_token_weights(tokens)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy/ComfyUI/comfy/text_encoders/qwen_image.py", line 62, in encode_token_weights
out, pooled, extra = super().encode_token_weights(token_weight_pairs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy/ComfyUI/comfy/sd1_clip.py", line 704, in encode_token_weights
out = getattr(self, self.clip).encode_token_weights(token_weight_pairs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy/ComfyUI/comfy/sd1_clip.py", line 45, in encode_token_weights
o = self.encode(to_encode)
^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy/ComfyUI/comfy/sd1_clip.py", line 297, in encode
return self(tokens)
^^^^^^^^^^^^
File "/root/comfy-env/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy-env/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy/ComfyUI/comfy/sd1_clip.py", line 257, in forward
embeds, attention_mask, num_tokens, embeds_info = self.process_tokens(tokens, device)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy/ComfyUI/comfy/sd1_clip.py", line 219, in process_tokens
emb, extra = self.transformer.preprocess_embed(emb, device=device)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy/ComfyUI/comfy/text_encoders/llama.py", line 593, in preprocess_embed
return self.visual(image.to(device, dtype=torch.float32), grid), grid
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy-env/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy-env/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy/ComfyUI/comfy/text_encoders/qwen_vl.py", line 425, in forward
hidden_states = block(hidden_states, position_embeddings, cu_seqlens_now, optimized_attention=optimized_attention)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy-env/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy-env/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy/ComfyUI/comfy/text_encoders/qwen_vl.py", line 252, in forward
hidden_states = self.attn(hidden_states, position_embeddings, cu_seqlens, optimized_attention)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy-env/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy-env/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy/ComfyUI/comfy/text_encoders/qwen_vl.py", line 195, in forward
qkv = self.qkv(hidden_states)
^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy-env/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy-env/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy/ComfyUI/comfy/ops.py", line 164, in forward
return self.forward_comfy_cast_weights(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy/ComfyUI/custom_nodes/ComfyUI-GGUF/ops.py", line 217, in forward_comfy_cast_weights
out = super().forward_comfy_cast_weights(input, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/comfy/ComfyUI/comfy/ops.py", line 157, in forward_comfy_cast_weights
x = torch.nn.functional.linear(input, weight, bias)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
RuntimeError: mat1 and mat2 shapes cannot be multiplied (748x1280 and 3840x1280)最終通過GitHubissue找到解決方案（感謝開源社區）：TextEncodeQwenImageEdit mat1 and mat2 shapes cannot be multiplied 問題解決方案，核心就是補全mmproj文件。建議大家直接按上文清單下載，避免重複踩坑。
三、工作流配置與效果測試
模型部署完成後，需配置對應的工作流。以下是我測試用的工作流截圖（可直接參考復刻）：
本次測試以「三圖編輯」為場景，重點驗證不同K採樣器步數對輸出效果的影響，測試環境為4090顯卡+Linux系統，具體結果如下：
3.1 20步採樣：速度快但效果差
- 運行時長：1分40秒
- 效果問題：人物手臂存在明顯割裂感；人物面部失真嚴重（如“馬爸爸”面部完全識別不出）
- 效果截圖：
3.2 40步採樣：效果略有提升但仍有缺陷
- 運行時長：4分37秒
- 效果問題：手部與手臂的割裂感未完全解決，仍存在明顯銜接瑕疵
- 效果截圖：
3.3 60步採樣：效果達標但耗時增加
- 運行時長：6分57秒
- 效果表現：手臂銜接問題基本解決；但人物面部仍與原角色有較大差異，且出現非預期的衣物顏色變化（如淺灰色衣物變為黑色）
- 效果截圖：
四、總結與後續優化方向
- 4090顯卡運行Qwen-Image-Edit-2511需優先選擇量化模型，按本文提供的國內鏡像鏈接下載可規避網絡問題，且mmproj文件不可遺漏；
- 採樣步數與效果、速度呈正相關：20步適合快速預覽，60步可解決核心瑕疵，但需接受更長耗時和人物臉部變更；
- 後續優化方向：可嘗試調整工作流中的提示詞精度、優化流程參數，或測試更高精度的量化模型（如Q2_K等），平衡效果與耗時。 如果大家在部署過程中遇到其他問題，歡迎在評論區交流～
