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Blended $/1M across tracked versions of this line.
Typical 3:1 output-to-input mix, per 1M tokens
Price as of 2026-05-10 · Source: minimax_official_pricing
General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.
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 major jump in...
minimax-m2.1 is a Text model from MiniMax (CN). HotON.ai tracks it at $0.29 per 1M input tokens and $0.95 per 1M output tokens, with a 1000K-token context window. Its composite efficiency score is 96/100 at an estimated $0.001 per successful task.
minimax-m2.1 is tracked at $0.29 per 1M input tokens and $0.95 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $0.78 per 1M tokens. Figures are illustrative demo data.
General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.
minimax-m2.1 supports up to a 1000K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, minimax-m2.1 is cheaper than 55% of models on input price and ranks #12 of 535 by overall efficiency.
Yes — deepseek-v4-flash is a lower-cost option at $0.28 per 1M output tokens, while still covering similar Text use cases. Compare them side by side on HotON.ai.
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HotON.ai — minimax-m2.1 (MiniMax): $0.29/1M input, $0.95/1M output, as of 2026-05-10. https://hoton.ai/en/models/minimax-minimax-m2-1Pricing is real (via the TestKey catalog, updated daily). Quality (Arena Elo) is real where the model is ranked on LMArena. Efficiency is a modeled composite of real price and context.