MiniMax: MiniMax M2
Analysis Summary
MiniMax M2 is a text model with a 204K context window, tool use, and function calling. Its strongest measured results are in coding and task execution, making it more compelling as a specialist engineering and agent workflow model than its overall intelligence measure suggests. The large context supports work across substantial documents or code inputs, while the listed pricing is moderate for a capable model.
It is suited to coding assistance, code review, and tool-driven automation where tasks can be evaluated against concrete outcomes. Strong performance on coding and tool-use measures also makes it a reasonable choice for bounded agent workflows. For nuanced editorial work or open-ended reasoning, teams should validate output quality rather than extrapolating from its coding strength.
Adopt it as a practical option for engineering and automation pilots. Use a stronger general model when the job depends on broad reasoning or high-stakes client-facing prose.
Assessed September 23, 2026
Editorial notes
MiniMax M2 combines strong coding and tool-use results with a 204K context window and competitive listed pricing; general reasoning measures are less strong than its specialist results.
The DFO score ranks models on the Artificial Analysis Intelligence Index and is refreshed as new models launch. The write-up and verdict are our own. Feedback?
DFO Verdict
MiniMax M2 combines strong coding and tool-use results with a 204K context window and competitive listed pricing; general reasoning measures are less strong than its specialist results.
Benchmarks
Artificial Analysis data refreshed Oct 12, 2026. Arena ratings from the Oct 2, 2026 text leaderboard, with style control. Bars: magenta = reasoning, ink = coding and agents, cyan = instructions and long context.
Artificial Analysis has not published coding or agentic results for MiniMax: MiniMax M2 yet. Until it does, the model sits below tested models on the Coding and AI Agents lists.
How MiniMax: MiniMax M2 compares
MiniMax: MiniMax M2 ranks #136 of 436 AI models we track for overall intelligence. Its 205K-token context window is larger than 58% of the models we list. At $0.30 per million input tokens it is cheaper than 43% of comparable models.
Dark bar = input · light bar = output, scaled to the priciest peer.
1M tokens ≈ 8 full-length novels or ~2,500 pages of business documents in a single request.
Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.30 | $0.000300 |
| Output | $1.20 | $0.001200 |
What would MiniMax: MiniMax M2 cost your business?
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A website chatbot handling around 100 customer conversations a day, a few short messages each.
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These numbers get smaller with the right architecture.
We route routine calls to cheap models and save MiniMax: MiniMax M2 for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout MiniMax: MiniMax M2
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 intelligence across general reasoning,..
Frequently asked questions about MiniMax: MiniMax M2
How much does MiniMax: MiniMax M2 cost?
MiniMax: MiniMax M2 costs $0.30 per million input tokens and $1.20 per million output tokens.
What is the context window of MiniMax: MiniMax M2?
MiniMax: MiniMax M2 has a context window of 204,800 tokens (205K).
What can MiniMax: MiniMax M2 do?
MiniMax: MiniMax M2 supports tool use and function calling.
Who created MiniMax: MiniMax M2?
MiniMax: MiniMax M2 is developed by MiniMax and was released on October 23, 2025.