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Qwen-Image-2.1 launches with open weights for image generation and editing

Alibaba’s Qwen team says the 7-billion-parameter model can generate and edit transparent images and use up to 10 reference images. The publisher genztech.blog reports that its license is non-commercial only.

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20 Sources, 19d ago, first seen 19d ago

TLDR

Alibaba’s Qwen team announced Qwen-Image-2.1’s open weights on September 20, 2026. The team says the model combines image generation and editing, supports transparent image layers and accepts up to 10 reference images. One example it describes uses colored circles to request three edits at once: removing a watch, changing hair color and replacing clothing. Qwen also announced ComfyUI support, and SGLang announced launch-day support in SGLang-Diffusion. Open weights come with a licensing restriction: genztech.blog reports that the model is licensed for non-commercial use only.

Combined views

81.5K

20 Sources, first seen 19d ago

447 likes32 comments110 saves43 reposts

Combined views

81.5K

20 Sources, first seen 19d ago

447 likes32 comments110 saves43 reposts

Sentiment

Positive64.8%35.2%Negative

Summary

Many accounts welcomed Qwen-Image-2.1 for its strong visuals, fast tool integrations, and hardware efficiency, while others objected to unclear licensing that restricts monetization and possible built-in censorship.

Based on 88 sentiment-bearing replies from 71 accounts across 8 conversations.

Sentiment

Positive64.8%35.2%Negative

Summary

Many accounts welcomed Qwen-Image-2.1 for its strong visuals, fast tool integrations, and hardware efficiency, while others objected to unclear licensing that restricts monetization and possible built-in censorship.

Based on 88 sentiment-bearing replies from 71 accounts across 8 conversations.

20 Sources

Qwen@Alibaba_QwenMeet Qwen-Image-2.1, the most balanced and cost-effective image generation model in the Qwen-Image series! Now open weights! 🎨 A unified model for both generation and editing, delivering top-tier quality in a lightweight package. Highlights: 👀 - Compact & exceptionally fast: A lightweight 7B architecture that outperforms most closed-source models, with drastically accelerated inference for multi-image inputs. - Native transparency: Natively generates and edits RGBA layers, enabling seamless compositing and text editing within transparent images. - Versatile, high-fidelity editing: Supports up to 10 reference images and precise local control while preserving strict fidelity for portraits and products. - Broad coverage & stunning aesthetics: Excels at panoramas, infographics, and virtual try-ons, delivering realistic textures and elegant typography. Start to create your next masterpiece with Qwen-Image-2.1! 🖼️ - Blog: https://qwen.ai/blog?id=qwen-image-2.1 - GitHub: https://github.com/QwenLM/Qwen-Image-2.1 - Model Scope: https://www.modelscope.cn/models/Qwen/Qwen-Image-2.1 - Hugging Face: https://huggingface.co/Qwen/Qwen-Image-2.119d
Mia@MiaAI_labQwen Image 2.1 open weights are now LIVE 🔥 https://huggingface.co/Qwen/Qwen-Image-2.119d
Teortaxes▶️ (DeepSeek 推特🐋铁粉 2023 – ∞)@teortaxesTexImpressive flex of image editing robustness from Qwen19d
AK@_akhaliqQwen-Image-2.1 is out on Hugging Face app: https://huggingface.co/spaces/akhaliq/Qwen-Image-2.119d
Chubby♨️@kimmonismusWe now have an open-weight 7B model that outperforms Nano Banana 2.0. Just let that sink in for a moment.19d
SGLang@sgl_projectDay-0 support for @Alibaba_Qwen’s Qwen-Image 2.1 is here in SGLang-Diffusion! 🖥️ Native precision on a single RTX 4090 24GB with CPU offload - 1024×1024 generation in 18.7s and image editing in 21.7s with 22.7 GiB peak GPU memory during requests. - On an RTX PRO 6000 96GB: 8.0s generation and 9.6s editing. 🎨 Text-to-image, multi-image editing, and transparent RGBA output—all with one checkpoint. ⚡ Native inference with TP/SP, LoRA, and OpenAI-compatible APIs. 40 denoising steps, one image per request, warmed HTTP latency including PNG output. No quantization. Cookbook and GPU-specific commands below 👇19d
cafkafk@cafkafkWake up babe Qwen-image-2.1 just dropped as open weight!!! https://qwen.ai/blog?id=qwen-image-2.119d
Ying Sheng@ying11231RT @sgl_project: Day-0 support for @Alibaba_Qwen’s Qwen-Image 2.1 is here in SGLang-Diffusion! 🖥️ Native precision on a single RTX 4090 24…19d
Techmeme@TechmemeAlibaba releases Qwen-Image-2.1, a 7B open-weight model it says outperforms most closed-source models, with native transparency and up to ten reference images (Qwen) (Visit Techmeme dot com for the link and full context!)19d
GENZ TECH@genztechblogQwen-Image 2.1 is out: a 7B DiT with a 64-channel RGBA VAE, so transparency comes out of the model, native 2048x2048, generation and editing in one checkpoint. The license is the catch: non-commercial only. https://genztech.blog/p/qwen-image-2-1-native-rgba-2k-research-license/19d
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    20 Sources

    Qwen@Alibaba_QwenMeet Qwen-Image-2.1, the most balanced and cost-effective image generation model in the Qwen-Image series! Now open weights! 🎨 A unified model for both generation and editing, delivering top-tier quality in a lightweight package. Highlights: 👀 - Compact & exceptionally fast: A lightweight 7B architecture that outperforms most closed-source models, with drastically accelerated inference for multi-image inputs. - Native transparency: Natively generates and edits RGBA layers, enabling seamless compositing and text editing within transparent images. - Versatile, high-fidelity editing: Supports up to 10 reference images and precise local control while preserving strict fidelity for portraits and products. - Broad coverage & stunning aesthetics: Excels at panoramas, infographics, and virtual try-ons, delivering realistic textures and elegant typography. Start to create your next masterpiece with Qwen-Image-2.1! 🖼️ - Blog: https://qwen.ai/blog?id=qwen-image-2.1 - GitHub: https://github.com/QwenLM/Qwen-Image-2.1 - Model Scope: https://www.modelscope.cn/models/Qwen/Qwen-Image-2.1 - Hugging Face: https://huggingface.co/Qwen/Qwen-Image-2.119d
    Mia@MiaAI_labQwen Image 2.1 open weights are now LIVE 🔥 https://huggingface.co/Qwen/Qwen-Image-2.119d
    Teortaxes▶️ (DeepSeek 推特🐋铁粉 2023 – ∞)@teortaxesTexImpressive flex of image editing robustness from Qwen19d
    AK@_akhaliqQwen-Image-2.1 is out on Hugging Face app: https://huggingface.co/spaces/akhaliq/Qwen-Image-2.119d
    Chubby♨️@kimmonismusWe now have an open-weight 7B model that outperforms Nano Banana 2.0. Just let that sink in for a moment.19d
    SGLang@sgl_projectDay-0 support for @Alibaba_Qwen’s Qwen-Image 2.1 is here in SGLang-Diffusion! 🖥️ Native precision on a single RTX 4090 24GB with CPU offload - 1024×1024 generation in 18.7s and image editing in 21.7s with 22.7 GiB peak GPU memory during requests. - On an RTX PRO 6000 96GB: 8.0s generation and 9.6s editing. 🎨 Text-to-image, multi-image editing, and transparent RGBA output—all with one checkpoint. ⚡ Native inference with TP/SP, LoRA, and OpenAI-compatible APIs. 40 denoising steps, one image per request, warmed HTTP latency including PNG output. No quantization. Cookbook and GPU-specific commands below 👇19d
    cafkafk@cafkafkWake up babe Qwen-image-2.1 just dropped as open weight!!! https://qwen.ai/blog?id=qwen-image-2.119d
    Ying Sheng@ying11231RT @sgl_project: Day-0 support for @Alibaba_Qwen’s Qwen-Image 2.1 is here in SGLang-Diffusion! 🖥️ Native precision on a single RTX 4090 24…19d
    Techmeme@TechmemeAlibaba releases Qwen-Image-2.1, a 7B open-weight model it says outperforms most closed-source models, with native transparency and up to ten reference images (Qwen) (Visit Techmeme dot com for the link and full context!)19d
    GENZ TECH@genztechblogQwen-Image 2.1 is out: a 7B DiT with a 64-channel RGBA VAE, so transparency comes out of the model, native 2048x2048, generation and editing in one checkpoint. The license is the catch: non-commercial only. https://genztech.blog/p/qwen-image-2-1-native-rgba-2k-research-license/19d
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