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-[ ][Documentation](../docs/source) and example scripts in [`examples`](../examples) are updated if necessary.
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-[ ] Throughput/latency benchmarks and quality evaluations are included where applicable.
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-[ ]**For reviewers:** If you're only helping merge the main branch and haven't contributed code to this PR, please remove yourself as a co-author when merging.
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-[ ] Please feel free to join our [Slack](https://join.slack.com/t/nunchaku/shared_invite/zt-3170agzoz-NgZzWaTrEj~n2KEV3Hpl5Q), [Discord](https://discord.gg/Wk6PnwX9Sm) or [WeChat](https://github.com/mit-han-lab/nunchaku/blob/main/assets/wechat.jpg) to discuss your PR.
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-[ ] Please feel free to join our [Slack](https://join.slack.com/t/nunchaku/shared_invite/zt-3170agzoz-NgZzWaTrEj~n2KEV3Hpl5Q), [Discord](https://discord.gg/Wk6PnwX9Sm) or [WeChat](https://huggingface.co/datasets/nunchaku-tech/cdn/blob/main/nunchaku/assets/wechat.jpg) to discuss your PR.
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## News
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-**[2025-09-04]** 🚀 Official release of **Nunchaku v1.0.0**! Qwen-Image now supports **asynchronous offloading**, reducing VRAM usage to as little as **3 GiB** with no performance loss. Check out the [tutorial](https://nunchaku.tech/docs/nunchaku/usage/qwenimage.html) to get started.
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-**[2025-08-27]** 🔥 Release **4-bit [4/8-step lightning Qwen-Image](https://huggingface.co/lightx2v/Qwen-Image-Lightning)**! Download on [Hugging Face](https://huggingface.co/nunchaku-tech/nunchaku-qwen-image) or [ModelScope](https://modelscope.cn/models/nunchaku-tech/nunchaku-qwen-image), and try it with our [example script](examples/v1/qwen-image-lightning.py).
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-**[2025-08-15]** 🔥 Our **4-bit Qwen-Image** models are now live on [Hugging Face](https://huggingface.co/nunchaku-tech/nunchaku-qwen-image)! Get started with our [example script](examples/v1/qwen-image.py). *ComfyUI, LoRA, and CPU offloading support are coming soon!*
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-**[2025-08-15]** 🚀 The **Python backend** is now available! Explore our Pythonic FLUX models [here](nunchaku/models/transformers/transformer_flux_v2.py) and see the modular **4-bit linear layer**[here](nunchaku/models/linear.py).
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-**[2025-07-31]** 🚀 **[FLUX.1-Krea-dev](https://www.krea.ai/blog/flux-krea-open-source-release) is now supported!** Check out our new [example script](./examples/flux.1-krea-dev.py) to get started.
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-**[2025-07-13]** 🚀 The official [**Nunchaku documentation**](https://nunchaku.tech/docs/nunchaku/) is now live! Explore comprehensive guides and resources to help you get started.
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-**[2025-06-29]** 🔥 Support **FLUX.1-Kontext**! Try out our [example script](./examples/flux.1-kontext-dev.py) to see it in action! Our demo is available at this [link](https://svdquant.mit.edu/kontext/)!
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-**[2025-06-01]** 🚀 **Release v0.3.0!** This update adds support for multiple-batch inference, [**ControlNet-Union-Pro 2.0**](https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro-2.0), initial integration of [**PuLID**](https://github.com/ToTheBeginning/PuLID), and introduces [**Double FB Cache**](examples/flux.1-dev-double_cache.py). You can now load Nunchaku FLUX models as a single file, and our upgraded [**4-bit T5 encoder**](https://huggingface.co/nunchaku-tech/nunchaku-t5) now matches **FP8 T5** in quality!
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<details>
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<summary>More</summary>
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-**[2025-06-01]** 🚀 **Release v0.3.0!** This update adds support for multiple-batch inference, [**ControlNet-Union-Pro 2.0**](https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro-2.0), initial integration of [**PuLID**](https://github.com/ToTheBeginning/PuLID), and introduces [**Double FB Cache**](examples/flux.1-dev-double_cache.py). You can now load Nunchaku FLUX models as a single file, and our upgraded [**4-bit T5 encoder**](https://huggingface.co/nunchaku-tech/nunchaku-t5) now matches **FP8 T5** in quality!
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-**[2025-04-16]** 🎥 Released tutorial videos in both [**English**](https://youtu.be/YHAVe-oM7U8?si=cM9zaby_aEHiFXk0) and [**Chinese**](https://www.bilibili.com/video/BV1BTocYjEk5/?share_source=copy_web&vd_source=8926212fef622f25cc95380515ac74ee) to assist installation and usage.
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-**[2025-04-09]** 📢 Published the [April roadmap](https://github.com/nunchaku-tech/nunchaku/issues/266) and an [FAQ](https://github.com/nunchaku-tech/nunchaku/discussions/262) to help the community get started and stay up to date with Nunchaku’s development.
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-**[2025-04-05]** 🚀 **Nunchaku v0.2.0 released!** This release brings [**multi-LoRA**](examples/flux.1-dev-multiple-lora.py) and [**ControlNet**](examples/flux.1-dev-controlnet-union-pro.py) support with even faster performance powered by [**FP16 attention**](#fp16-attention) and [**First-Block Cache**](#first-block-cache). We've also added compatibility for [**20-series GPUs**](examples/flux.1-dev-turing.py) — Nunchaku is now more accessible than ever!
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