MiniMax: MiniMax M2
Analysis Summary
MiniMax M2 is a text model with a 204.8K context window, tool use, and function calling. Its measured coding, mathematics, instruction-following, long-context, and agentic results are substantially stronger than its general intelligence index suggests, giving it a useful profile for technical workflows and multi-step execution.
The model fits software maintenance, code generation, repository analysis, structured research, and agents that need reliable tool interaction over long inputs. Its context capacity supports substantial documents or codebases, while pricing is competitive enough for repeated production calls. It remains below frontier general-purpose models for broad reasoning and should receive validation on customer-facing copy and high-stakes decisions.
Adopt it as a practical coding and agent specialist, particularly where context length and cost matter. Pair it with a stronger model for the most difficult reasoning tasks.
Assessed September 7, 2026
Editorial notes
MiniMax M2 combines strong coding and tool-use results with a 204.8K context, function calling, and competitive pricing. Its general intelligence is below flagship level, but it is a capable choice for coding agents and structured automation.
Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?
DFO Verdict
MiniMax M2 combines strong coding and tool-use results with a 204.8K context, function calling, and competitive pricing. Its general intelligence is below flagship level, but it is a capable choice for coding agents and structured automation.
Benchmark scores
Magenta = intelligence · Ink = technical/agentic · Cyan = content & long-context · Grey = community benchmarks. Data: Artificial Analysis, Hugging Face.
18.6 Intelligence Index·78.3 Math Index
How MiniMax: MiniMax M2 compares
MiniMax: MiniMax M2 ranks #145 of 438 AI models we track for overall intelligence. Its 205K-token context window is larger than 55% of the models we list. At $0.26 per million input tokens it is cheaper than 49% 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.
Strongest on value. The pulled-in technical corner is the trade-off, and if the shape matters more than the price, this is your model.
Compare shapes side-by-side →Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.26 | $0.000255 |
| Output | $1.02 | $0.001020 |
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.
Full calculator with 776 models → Price Calculator
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 $0.26 per million input tokens and $1.02 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.