8-bit affine (group size 64) conversion of MiniMax-H3's FL2VA checkpoint for mlx-serve, running natively on Apple Silicon. Text-to-audio-video: the DiT denoises video and stereo audio jointly in one packed sequence.

Self-contained: weights, both VAEs and the tokenizer in one directory. Upstream splits these across Comfy-Org/MiniMax-H3 (weights, no tokenizer) and MiniMaxAI/MiniMax-H3 (tokenizer).

Quantized: the DiT and text-encoder matmul weights. Kept dense: gathered embedding tables, the checkpoint's fp32 islands (patch projections, output heads, time embedder) and both VAEs.

Note that quantization here buys FOOTPRINT, not speed — the workload is compute-bound at roughly 192,000 FLOPs per weight byte.

These are MODIFIED files. The transformer and text encoder are quantized to 8-bit; see MODIFICATIONS.md for the full list. The VAEs and tokenizer are unmodified copies.

turbo_lora.safetensors is included. It is a 4-step distillation adapter trained by larryvrh and licensed Apache-2.0, copied byte for byte from that repo's minimax_h3_turbo_4step_ema_ckpt850.safetensors and renamed so mlx-serve finds it inside the pack. Nothing about it was changed.

It samples in 4 to 8 steps instead of the usual 16 to 30 (larryvrh notes 4 is already sharp on this checkpoint; earlier ones needed 6 to 8). Measured on an M4 Max at 960x544, 39 frames, one prompt: 188s of sampling at 16 steps without it against 95s at 4 steps with it, so roughly 2x on sampling and 1.8x on the whole request once staging and VAE decode are counted. Per step it is about 20% slower, because the adapter is summed at runtime rather than folded into the weights and it turns off mlx-serve's step-caching recipe. The win is the step count, not the step.

Treat it as a preview. This is the EMA weighting of checkpoint 850, which larryvrh recommends as the cleanest of the round; the non-EMA file of the same step is sharper still but over-sharpened, and their notes describe plastic skin and over-sharp grain as the round's known failure modes. Their guidance if you hit either: nudge LoRA strength down to 0.8-0.95 for grain, up to 1.05-1.2 for blurry ghosting.

Request it with "turbo": true, or tick Turbo in the mlx-serve app's video pane. It stacks with your own style LoRAs rather than replacing them.

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