boogu-image-turbo-mflux-q4
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From language to images, open weights to APIs. Understand capabilities and compare real costs.
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**MFlux** runs the latest state-of-the-art generative image models locally on your Mac in native MLX. MFlux is open source and free. > [!NOTE] > Community conversion by MFlux-Community -- not an official release from the original model's authors. The original model's license applies unchanged, see License. Standard MFlux quantization uses MLX affine quantization (8-bit) across the text encoder, transformer and VAE. The quantization level is stored in the weights, so no `--quantize` flag is needed.
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基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。
基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。
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**MFlux** runs the latest state-of-the-art generative image models locally on your Mac in native MLX. MFlux is open source and free. > [!NOTE] > Community conversion by MFlux-Community -- not an official release from the original model's authors. The original model's license applies unchanged, see License. Standard MFlux quantization uses MLX affine quantization (4-bit) across the text encoder, transformer and VAE. The quantization level is stored in the weights, so no `--quantize` flag is needed.
基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。
基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。
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Adjust provider, category or input/output filters. New models are added continuously.
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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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