Initial release of M3 with 428B parameters, native multimodal training, and MiniMax Sparse Attention enabling 1M context with 15× decode speedup over M2.
M3 introduces MiniMax Sparse Attention to enable 1M-token context at approximately 1/20th the compute cost of previous generation. Native multimodal training on interleaved data with interactive user-simulator tuning.
MiniMax has released M3, a multimodal model with approximately 428 billion parameters and 23 billion activated parameters. The model supports a 1 million token context window and uses MiniMax Sparse Attention to achieve 9× prefill and 15× decode speedups compared to its predecessor M2.
MiniMax has released M3, a multimodal foundation model supporting text, image, and video inputs with a 1-million-token context window. The model costs $0.30 per million input tokens and $1.20 per million output tokens, available through OpenRouter.