MiniMax-H3-ref2va-pruned-zs05-comfy-fp8.safetensors
更新2026-08-29 16:13发布时间2026-08-29 16:13
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MiniMax-H3-ref2va-pruned-zs05-comfy-fp8.safetensors - 1
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Lorena
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Other
基础模型
MiniMax H3
发布时间
2026-08-29 16:13
文件签名
30f67afd905a1066513c5a2e6c6e144ab7d44ef9c015e31a49ddf0a5df562f4b
MiniMax-H3-ref2va-pruned-zs05-comfy-fp8.safetensors
19.52 GB

license: other license_name: minimax-h3-community-license license_link: https://huggingface.co/Comfy-Org/MiniMax-H3 base_model:

  • MiniMaxAI/MiniMax-H3 tags:
  • comfyui
  • comfy-native
  • comfy-quant
  • minimax-h3
  • z-image
  • video-generation
  • audio-video
  • merge pipeline_tag: text-to-video

MiniMax-H3 × Z-Image — spatial detail graft (comfy-native)

The comfy-native cuts of the MiniMax-H3 × Z-Image graft: Z-Image's spatial-attention profile on H3's engine — richer sets and textures, same identity, no per-shot sharpening creep. Full story, demos and verification on the GGUF page.

Load with the plain Load Diffusion Model node, ComfyUI 0.32+. Files are the pruned H3 builds with the graft baked in (zs05 = late-block gains, dose 0.5):

  • bf16 — the master (ref2va)
  • comfy-fp8 / fp8e5m2 — fp8 scaled
  • comfy-int8 / int8_convrot — the fast pick on RTX 50
  • comfy-w4a8 / w4a4 / nvfp4 — 4-bit family for 16 GB cards (w4a8 is the quality pick; nvfp4 is Blackwell-native, emulated elsewhere)
  • comfy-mxfp8 — 8-bit microscaling, Blackwell-specialized; little benefit on older architectures
  • fl2va and ref2va variants where both exist; picking rules are identical to stock H3

RTX 30/40: the GGUF repo is 4–8× faster than any 4-bit comfy-native arm on Ampere.

Made by joeygambino. Questions: open a discussion — I answer.

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