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Comparison of MiniMax: MiniMax-01, MiniMax: MiniMax M2, MiniMax: MiniMax M2.1
3 modelsminimaxMiniMax: MiniMax-01Remove ×minimaxMiniMax: MiniMax M2Remove ×minimaxMiniMax: MiniMax M2.1Remove ×
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 is a compact, high-efficiency large language model optimized for end-to-end coding and agentic workflows. With 10 billion activated parameters (230 billion total), it delivers near-frontier…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…
DateJan 15, 2025ListedOct 23, 2025ListedDec 23, 2025Listed
Listed rate$0.20 in / $1.10 out/ 1M tokensMinimax · via OpenRouter · all routes ↗minimax$0.255 in / $1.02 out/ 1M tokensMinimax · via OpenRouter · all routes ↗minimax/fp8 · quantization=fp8$0.30 in / $1.20 out/ 1M tokensMinimax · via OpenRouter · all routes ↗minimax/fp8 · quantization=fp8
Provider endpoints2 endpoints →3 endpoints →3 endpoints →
Context window1M204.8K204.8K
Max output900.2K131.1K131.1K
Parameters———
Tool callingNot reportedSupportedSupported
Structured outputNot reportedSupportedSupported
Image inputSupportedNot reportedNot reported
ReasoningNot reportedSupportedSupported
Prompt cachingNot reportedNot reportedSupported
Open weightsSupportedSupportedSupported

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