MiniMax H3 FP8 (E4M3FN) Quantized
Based on testing (this model and pruned_fp8), the minimal steps to get results similar to Lightx2v using 4-step LoRAs is 5step & 5steps.
The sweet spot for quality and speed is 8step and 8steps. This quantization requires a minimum of 8step.
- Sampler: dpmpp_2m
- Scheduler: sgm_uniform
| 5-Step pruned fp8 | 8-Step this model |
|---------|-------|
| | |
FP8 quantization of the MiniMax H3 fl2va (first-last-frame to video+audio)
diffusion checkpoint.
Your browser does not support the video tag.
Original model: MiniMaxAI/MiniMax-H3
File sizes
| Variant | Download |
|---------|------|
| minimax_h3_fl2va_fp8_e4m3fn.safetensors| Download |
|minimax_h3_fl2va_pruned_fp8_scaled.safetensors | Download
Left at native precision (quality-critical)
| Tensors | Dtype | Note |
|---------|-------|--------|
| adaln_proj.linear.* (100 tensors) | BF16 | Per-block modulation, largest single weight |
| token_refiner.* (17 tensors) | BF16 | Text embedding refinement, 2 layers only |
| condition_proj.* (2 tensors) | BF16 | Cross-modal conditioning bridge |
| All norm weights (norm1, norm2, q_norm, k_norm, final_norm) | BF16 | 104 tensors, tiny and precision-sensitive |
| All biases | BF16 | 56 tensors |
| time_embedder.* (4 tensors) | FP32 | Timestep signal, original precision preserved |
| video_patch_proj., audio_patch_proj. (4 tensors) | FP32 | Input/output projections |
| final_layer._out. (4 tensors) | FP32 | Decoder output heads |
| rope.inv_freq (1 tensor) | FP32 | Position encoding |