MiniMax-M3 is a native multimodal MoE model. The original model card describes it as a ~428B parameter model with ~23B activated parameters and 1M context support.
License
This quantized checkpoint follows the license terms of the base model,
MiniMaxAI/MiniMax-M3
. The Hugging Face model-card metadata uses
license: other
because the MiniMax community license is not one of the Hub's enumerated license identifiers.
Model Optimizations
This checkpoint uses FP8 dynamic quantization to reduce memory and disk requirements while preserving model quality. Validation below compares this quantized checkpoint against the BF16
MiniMaxAI/MiniMax-M3
baseline.
Evaluation
The model was evaluated against BF16
MiniMaxAI/MiniMax-M3
. Scores are averaged across seeds.
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