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)
| 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 |
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Model tree for rzgar/minimax_h3_ref2va_fp8_e4m3fn
Base model
MiniMaxAI/MiniMax-H3