MiniMax M1

minimax-m1
by minimax|Created Jun 23, 2025

MiniMax-M1 is a large-scale, open-weight reasoning model with 456B total parameters and 45.9B active per token, leveraging a hybrid Mixture-of-Experts (MoE) architecture and a custom "lightning attention" mechanism. It supports context windows up to 1 million tokens and is optimized for long-context understanding, software engineering, agentic tool use, and mathematical reasoning. The model is trained via a custom reinforcement learning pipeline (CISPO) and demonstrates strong performance on FullStackBench, SWE-bench, MATH, GPQA, and TAU-Bench.

Pricing

Pay-as-you-go rates for this model. More details can be found here.

Input Tokens (1M)

$0.40

Output Tokens (1M)

$0.96

Capabilities

Input Modalities

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Output Modalities

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Usage Analytics

Token usage across the last 30 active days

Throughput

Time-To-First-Token (TTFT)