MiniMax: MiniMax M2.7
Analysis Summary
MiniMax M2.7 is a text model with strong coding capability, a 204,800-token context window, and built-in tool use and function calling. The combination is well suited to software engineering, code transformation, test creation, repository discussion, and structured assistants that need more than one conversational turn.
Its main operational limitation is the gap between coding strength and agentic reliability. Design for Online would use it for supervised coding agents, technical support, and repeatable automations with clear schemas and review checkpoints, rather than unrestricted autonomous execution. The pricing is attractive for regular production traffic, especially when context requirements exceed smaller models. It is a practical specialist and value pick, while premium reasoning tasks may still warrant a stronger flagship.
Assessed August 9, 2026
Editorial notes
MiniMax M2.7 pairs strong coding with a 204K context, tool use, and function calling at accessible pricing. Its agentic capability trails its programming strength, making supervised engineering and structured automation the best fit.
Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?
DFO Verdict
MiniMax M2.7 pairs strong coding with a 204K context, tool use, and function calling at accessible pricing. Its agentic capability trails its programming strength, making supervised engineering and structured automation the best fit.
How MiniMax: MiniMax M2.7 compares
MiniMax: MiniMax M2.7 ranks #72 of 427 AI models we track for overall intelligence, #61 of 200 for coding, #74 of 182 for agentic tasks. 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 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.
Strongest on business fit. 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 | $0.30 | $0.000300 |
| Output | $1.20 | $0.001200 |
What would MiniMax: MiniMax M2.7 cost your business?
Pick the job that looks most like yours, then fine-tune with the sliders. Estimates update live.
A website chatbot handling around 100 customer conversations a day, a few short messages each.
Full calculator with 713 models → Price Calculator
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 $0.30 per million input tokens and $1.20 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 #61 of 200 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.