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@@ -37,6 +37,8 @@ library_name: diffusers
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  ![teaser](https://github.com/mit-han-lab/nunchaku/raw/refs/heads/main/assets/teaser.jpg)
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  SVDQuant is a post-training quantization technique for 4-bit weights and activations that well maintains visual fidelity. On 12B FLUX.1-dev, it achieves 3.6× memory reduction compared to the BF16 model. By eliminating CPU offloading, it offers 8.7× speedup over the 16-bit model when on a 16GB laptop 4090 GPU, 3× faster than the NF4 W4A16 baseline. On PixArt-∑, it demonstrates significantly superior visual quality over other W4A4 or even W4A8 baselines. "E2E" means the end-to-end latency including the text encoder and VAE decoder.
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  ## Method
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  #### Quantization Method -- SVDQuant
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  ![teaser](https://github.com/mit-han-lab/nunchaku/raw/refs/heads/main/assets/teaser.jpg)
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  SVDQuant is a post-training quantization technique for 4-bit weights and activations that well maintains visual fidelity. On 12B FLUX.1-dev, it achieves 3.6× memory reduction compared to the BF16 model. By eliminating CPU offloading, it offers 8.7× speedup over the 16-bit model when on a 16GB laptop 4090 GPU, 3× faster than the NF4 W4A16 baseline. On PixArt-∑, it demonstrates significantly superior visual quality over other W4A4 or even W4A8 baselines. "E2E" means the end-to-end latency including the text encoder and VAE decoder.
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+ `svdq-int4-flux.1-schnell` is an INT4-quantized version of [`FLUX.1-schnell`](https://huggingface.co/black-forest-labs/FLUX.1-schnell), which can generate an image based on a text description.
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  ## Method
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  #### Quantization Method -- SVDQuant
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