MiniMax-M3 Vision

This repository packages the Tower and Projector from MiniMax M3.

Contents

File Tensors What it holds
model.safetensors 515 MiniMax-M3 vision tower
projector.safetensors 8 multi_modal_projector and remapped patch_merge_mlp
projector_config.json, projector.py Projector shapes and loader
config.json, preprocessor_config.json Vision-only model and image-processing configuration
LICENSE MiniMax Community License

Architecture

Component Details
Tower CLIP-style ViT, 32 layers, 1280 hidden, 16 heads, 5120 intermediate, patch size 14, Conv3d patch embed, 3D RoPE, GELU, image size 2016
Token compression 2x2 spatial merge, temporal patch size 2
Projector Linear(1280, 6144), GELU, Linear(6144, 6144), flatten four 6144-wide patches, Linear(24576, 6144), GELU, Linear(6144, 6144)

The class is MiniMaxM3VLVisionModel (model_type minimax_m3_vl_vision). last_hidden_state is the raw 1280-wide Tower tokens. At 448 the bench reports 1280-wide Tower tokens, 5120-wide merged tokens (2x2 of 1280), and 6144-wide projected tokens. projector_config.json records input_size 1280, hidden_size 6144, output_size 6144, and merged_hidden_size 24576.

Usage

See examples/inference.py for image feature extraction.

Validation

The parity script compares all 515 Tower tensors and eight Projector tensors with the pinned parent checkpoint using torch.equal.

Reproduction

The export script reads vision_tower.vision_model.* from shard 59 of MiniMaxAI/MiniMax-M3. It remaps encoder.layers to layers and embeddings.patch_embedding to embeddings.proj, then writes 515 Tower tensors. The Projector comes from multi_modal_projector.* and patch_merge_mlp.* in shards 26 and 59, with merge linear names remapped, for eight tensors. The original BF16 weights are preserved.

Credits

MiniMax released the MiniMax-M3 weights and the native Transformers implementation.

License

MiniMax Community License, the same license as the source model.

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