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TText generation▧Image generation▷Video generation⌘Code generation◖Speech synthesis♫Music generation⬡3D modeling▤Document analysis
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🌐 Website  |  🐙 GitHub  |  🤗 Hugging Face  |  🤖 ModelScope  |  🎨 Civitai  |  🎮 Discord QuantFunc INT4 compresses Krea-2-Turbo to about a quarter of its 16-bit size. In our visual comparisons, composition, detail, color and style stay close to the 16-bit baseline, roughly on par with FP8 and INT8 ConvRot. > End-to-end includes text encoder, denoising and VAE. Text encoder and VAE are not part of the QuantFunc plugin's acceleration path today. Actual speed varies with resolution, steps, driver, software version and hardware.

Image generation
Input Text→ Output Image
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🌐 Website  |  🐙 GitHub  |  🤗 Hugging Face  |  🤖 ModelScope  |  🎨 Civitai  |  🎮 Discord QuantFunc INT4 cuts MiniMax H3's core weight precision from 16-bit to 4-bit. Character detail, style fidelity and fast motion stay clear and coherent, while H3's native video+audio generation is fully preserved. In our internal FL2VA evaluation, QuantFunc INT4 vs the BF16 baseline (same prompt, same seed) measures ~**23.7 dB PSNR**.

Video generation
Input Text→ Output Video
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These are **quantized derivative weights** of `Qwen/Qwen-Image-Edit-2511` (**Qwen-Image-Edit-2511**). > **Disclaimer:** "Nunchaku" / "SVDQuant" name the *quantization method/format* (the open-source SVDQuant work by MIT HAN Lab, Apache-2.0). This repository is an independent re-quantization and is **not affiliated with, sponsored by, or endorsed by MIT HAN Lab or the Nunchaku project**. Official Nunchaku releases are under the `nunchaku-ai` / `nunchaku-tech` namespaces. 🤗 Hugging Face  |  🤖 ModelScope  |  💻 GitHub  |  💬 WeChat (微信)  |  🎮 Discord

Image editing
Input Image→ Output Image
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Separate input, output and cache rates, then estimate the same workload. Image, audio and video rates may use items, duration or resolution rather than tokens.

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