MiniMax: MiniMax M2.7
Analysis Summary
MiniMax M2.7 is a text model with a 204K context window, tool use, and function calling. Its coding index is a clear strength, while its agentic index is considerably lower, indicating that coding performance should not be treated as proof of dependable autonomous execution. The supplied data does not include content-quality, instruction-following, or multimodal benchmark results.
This profile suits software development assistance and structured coding tasks where teams can review the output. Tool calling makes it usable in workflows that need external actions, but the weaker agentic result argues for close controls around long, unsupervised sequences. Listed pricing is relatively low, which supports testing it on routine development volume. Adopt it as a coding-focused secondary model and evaluate completion quality, tool reliability, and editorial performance separately before expanding it to client-facing work.
Assessed September 23, 2026
Editorial notes
MiniMax M2.7 pairs a strong coding index with tool and function calling at low listed prices, though its agentic result is much weaker and content benchmarks are not supplied.
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 M2.7 pairs a strong coding index with tool and function calling at low listed prices, though its agentic result is much weaker and content benchmarks are not supplied.
Benchmarks
Artificial Analysis data refreshed Nov 7, 2026. Arena ratings from the Oct 28, 2026 text leaderboard, with style control.
Artificial Analysis no longer lists this model, so its indexes are converted from their older scale to stay comparable.
How MiniMax: MiniMax M2.7 compares
MiniMax: MiniMax M2.7 ranks #116 of 447 AI models we track for overall intelligence, #64 of 199 for coding, #91 of 181 for agentic tasks. Its 205K-token context window is larger than 56% of the models we list. At $0.21 per million input tokens it is cheaper than 48% 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 | $0.21 | $0.000210 |
| Output | $0.84 | $0.000840 |
What would MiniMax: MiniMax M2.7 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 M2.7 for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout MiniMax: MiniMax M2.7
MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity and continuous improvement. Built to actively participate in its own evolution, M2.7 integrates advanced agentic capabilities through multi-agent..
Frequently asked questions about MiniMax: MiniMax M2.7
How much does MiniMax: MiniMax M2.7 cost?
MiniMax: MiniMax M2.7 costs $0.21 per million input tokens and $0.84 per million output tokens.
What is the context window of MiniMax: MiniMax M2.7?
MiniMax: MiniMax M2.7 has a context window of 204,800 tokens (205K).
Is MiniMax: MiniMax M2.7 good for coding?
On our coding benchmark index, MiniMax: MiniMax M2.7 ranks #64 of 199 models, placing it in the broader range of the field for code generation and debugging.
What can MiniMax: MiniMax M2.7 do?
MiniMax: MiniMax M2.7 supports tool use and function calling.
Who created MiniMax: MiniMax M2.7?
MiniMax: MiniMax M2.7 is developed by MiniMax and was released on March 18, 2026.