rzgar/minimax_h3_ref2va_fp8_e4m3fn

🤗 Hugging Face 来源image-to-videoapache-2.076 GBother✓ 10 个校验和今天更新
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MiniMax H3 Ref2VA (mxfp8 & fp16attn_fp8)

Quantized versions of the MiniMax H3 Ref2VA (reference-to-video-audio) diffusion model. Both keep the text-conditioning path (token_refiner, conditioning projections, audio heads) in full precision.

Latest comfy version improves audio quality at low steps.

minimal 5 step (talking heads, less motions) | balanced 8-steps (shift 8) | Action-rich scenes above 12 (shift max 12)

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File Download Note
minimax_h3_ref2va_fp16attn_fp8.safetensors Download 28.7GB FP16 attention + FP8-E4M3 MLP
minimax_h3_ref2va_mxfp8.safetensors Download 47.6GB E4M3 weights, E8M0 block scales

Comparison

fp16attn_fp8 mxfp8
Size 28.7 GB 47.6 GB
Base checkpoint pruned fp8_scaled (curve-form, adaln_t_table) full bf16 (time-embedder)
Attention (qkv/out) FP16 (exact) MXFP8 (block-quantized)
MLP (fc1/fc2) FP8-E4M3 per-tensor absmax MXFP8 block-quantized
Quant scale granularity per-tensor per-32 block (better outlier handling)
input_scale calibrated (fc1), fpmm on fc2 1.0 identity (150 layers)
token_refiner / conditioning full precision full precision
Relative precision higher than pruned fp8, attn lossless highest of the two (finer scales)
Memory footprint lighter (faster load, less streaming) heavier
Best for everyday use / speed-first setups maximum quality per weight bit