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Comparison of MiniMax: MiniMax-01, MiniMax: MiniMax M2.1, MiniMax: MiniMax M2
3 modelsminimaxMiniMax: MiniMax-01Remove ×minimaxMiniMax: MiniMax M2.1Remove ×minimaxMiniMax: MiniMax M2Remove ×
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-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…
DateJan 15, 2025ListedDec 23, 2025ListedOct 23, 2025Listed
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$0.255 in / $1.02 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 reportedSupportedNot reported
Open weightsSupportedSupportedSupported

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