QwenLM/Qwen-Image-2.1

选用指南

AI 根据 README 整理 · 2026/10/16 21:31:33

使用方式

通过 Python 使用 Diffusers 库加载模型进行文本到图像生成和图像编辑，也可通过 ComfyUI 或 vLLM-Omni 等工具使用。

查看 README 依据

Visit the [Qwen-Image-2.1 Pro API page](https://modelstudio.console.alibabacloud.com/ap-southeast-1/model/market/detail/qwen-image-2.1-pro?serviceSite=international&ref=list) or [Qwen-Image-2.1 Turbo API page](https://modelstudio.console.alibabacloud.com/ap-southeast-1/model/market/detail/qwen-image-2.1-turbo?serviceSite=international&ref=list) for access and usage details. ## Quick Start ### Requirements ```bash pip install torch>=2.4.0 pip install transformers>=5.17 pip install git+https://github.com/huggingface/diffusers pip install accelerate pip install pillow ```

- 2026.09.20: [ComfyUI](https://github.com/Comfy-Org/ComfyUI) natively supports Qwen-Image-2.1 from Day 0. Compatible weights at [Comfy-Org/Qwen-Image-2.1](https://huggingface.co/Comfy-Org/Qwen-Image-2.1), with example workflows for [text-to-image](https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_qwen_image_2_1_t2i.json) and [image editing](https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_qwen_image_2_1_image_edit.json).

- 2026.09.20: [vLLM-Omni](https://github.com/vllm-project/vllm-omni) supports high-performance Qwen-Image-2.1 inference from Day 0, with step-wise execution, prefix KV caching, CUDA Graph decode, FP8 quantization, and TP/Ulysses parallelism. - 2026.09.20: [SGLang](https://github.com/sgl-project/sglang) provides Day-0 native support for Qwen-Image-2.1, including prefix caching, Cache-DiT, CUDA graphs, TP/Ulysses/Ring/CFG parallelism, and component offload. See [PR #39983](https://github.com/sgl-project/sglang/pull/39983).

部署要求

需要安装 torch>=2.4.0、transformers>=5.17、diffusers、accelerate 和 pillow，并使用 CUDA 设备运行。

查看 README 依据

Visit the [Qwen-Image-2.1 Pro API page](https://modelstudio.console.alibabacloud.com/ap-southeast-1/model/market/detail/qwen-image-2.1-pro?serviceSite=international&ref=list) or [Qwen-Image-2.1 Turbo API page](https://modelstudio.console.alibabacloud.com/ap-southeast-1/model/market/detail/qwen-image-2.1-turbo?serviceSite=international&ref=list) for access and usage details. ## Quick Start ### Requirements ```bash pip install torch>=2.4.0 pip install transformers>=5.17 pip install git+https://github.com/huggingface/diffusers pip install accelerate pip install pillow ```

已知限制

Turbo 版本使用固定的8步采样调度，设置 num_inference_steps 不会覆盖其保存的调度。

查看 README 依据

The editing example loads a yacht sketch and turns it into a photorealistic image. Both calls use the saved **8-step schedule** and the default CFG=1 setting. Setting `num_inference_steps` alone does not override Turbo's saved schedule. See the [Turbo model card](https://huggingface.co/Qwen/Qwen-Image-2.1-Turbo) for more details. The following examples use the original **Qwen-Image-2.1** checkpoint. ### Text-to-Image ```python import torch from diffusers import QwenImage21Pipeline pipe = QwenImage21Pipeline.from_pretrained( "Qwen/Qwen-Image-2.1", torch_dtype=torch.bfloat16