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genmo/mochi-1-preview
for the SceneWorks native MLX runtime (mlx-gen-mochi). The AsymmDiT transformer ships as three
self-contained, pre-quantized tiers; the T5-XXL text encoder and AsymmVAE are shared across
tiers (hosted once as siblings, not duplicated per tier).q4/ transformer/model.safetensors + split_model.json + quantize_config.json (~9 GB)
q8/ transformer/model.safetensors + split_model.json + quantize_config.json (~12 GB)
bf16/ transformer/model.safetensors + split_model.json (~19 GB)
text_encoder/ T5-XXL, bf16 (2-shard) + model.safetensors.index.json (~9.5 GB)
vae/ AsymmVAE decoder, bf16 (~0.9 GB)
tokenizer/ T5 SentencePiece tokenizerq4/); the shared text_encoder/, vae/,
and tokenizer/ resolve from the parent as siblings of the tier subdirs.| Tier | Transformer precision | Approx. size |
|---|---|---|
q4 | 4-bit affine (group 64), 573 quantized Linears | ~9 GB |
q8 | 8-bit affine (group 64), 573 quantized Linears | ~12 GB |
bf16 | dense bf16 | ~19 GB |
split_model.json records the quant selection (quantized, quantization_bits,
quantization_group_size); a tier dir is the quant selection (no on-the-fly requantization).text_encoder/ — T5-XXL (google/t5-v1_1-xxl, 24-layer encoder, d_model=4096) hosted in
bf16 (2-shard set + a matching model.safetensors.index.json), bit-identical to
round-to-bf16 of the upstream fp32 weights (the precision the reference pipeline loads at).vae/ — AutoencoderKLMochi decoder in bf16.tokenizer/ — the T5 SentencePiece tokenizer.genmo/mochi-1-preview. Licensed
Apache-2.0, matching the upstream Mochi 1 release. Weights are unchanged apart from the per-tier
quantization of the transformer and the dtype/shard repackaging described above.