Built with Qwen. Non-commercial research and evaluation use only (Qwen Research License, see LICENSE and NOTICE). An NVFP4 quantization of Qwen/Qwen-Image-2.1, made from the official BF16 weights with SVDQuant + GPTQ and calibrated on both text-to-image prompts and image edits. Both large components run on native Blackwell FP4 tensor cores, and the pipeline loads with a single DiffusionPipeline.frompretrained call. At 512x512 on an RTX PRO 6000 Blackwell it is about 1.7x faster than BF16 and needs about 40% less VRAM, and it matches BF16 closely on text-to-image, typography and edits, including a hard recolor edit that earlier 4-bit text encoders failed. trustremotecode=True loads two small…
Independent publisher
Josep López
joseplcam
Computer Vision/NLP/Affective Computing
Models in Library1
Datasets in Library0
Models on Hugging Face3
Followers1
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Published tasks: Text to image.
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