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Comparison of MiniMax: MiniMax-01, MiniMax: MiniMax M2.1, MiniMax-M3
3 modelsminimaxMiniMax: MiniMax-01Remove ×minimaxMiniMax: MiniMax M2.1Remove ×MiniMaxAIMiniMax-M3Remove ×
What’s differentMiniMax-01 is a combines MiniMax-Text-01 for text generation and MiniMax-VL-01 for image understanding. It has 456 billion parameters, with 45.9 billion parameters activated per inference, and can handle a…MiniMax-M2.1 is a lightweight, state-of-the-art large language model optimized for coding, agentic workflows, and modern application development. With only 10 billion activated parameters, it delivers a…MiniMax-M3 is a native multimodal model with 1M context. It has ~428B parameters and ~23B activated parameters.
DateJan 15, 2025ListedDec 23, 2025ListedJun 2, 2026Listed
Listed rate$0.20 in / $1.10 out/ 1M tokensMinimax · via OpenRouter · all routes ↗minimax$0.30 in / $1.20 out/ 1M tokensMinimax · via OpenRouter · all routes ↗minimax/fp8 · quantization=fp8$0.28 in / $1.10 out/ 1M tokensdeepinfra · via Hugging Face · all routes ↗
Provider endpoints2 endpoints →3 endpoints →7 endpoints →
Context window1M204.8K1M
Max output900.2K131.1K—
Parameters———
Tool callingNot reportedSupportedSupported
Structured outputNot reportedSupportedSupported
Image inputSupportedNot reportedSupported
ReasoningNot reportedSupportedNot reported
Prompt cachingNot reportedSupportedNot reported
Open weightsSupportedSupportedSupported

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