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MiniMax-M

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MiniMax 모델 공개 가중치
입력텍스트텍스트

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무엇인가

MiniMax-M1 is an open-weight reasoning model MiniMax released in June 2025. MiniMax was founded in Shanghai in 2021 by Yan Junjie and others. M1 uses a hybrid attention design that combines standard full-attention layers with linear-attention layers to cut the compute cost of long-sequence reasoning, and its stated context window reaches the million-token range. With 456B total parameters activating about 46B per token, it is a large-scale MoE reasoning model whose weights are released under an open licence. The company also runs generation product lines such as Hailuo.

기억할 만한 이유

It mixes linear and full attention and pushes context to a million tokens to cut the cost of long-sequence reasoning; among the larger open-weight reasoning models, it is a concrete landing of the open-weight camp on the reasoning track.

주요 사양

Parameters
456B (MoE, ~46B active)
Context window
1M tokens
Architecture
Hybrid linear and full attention
Open weights
Yes

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