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MiniMax: MiniMax M2.7

minimax/minimax-m2.7

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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 collaboration, enabling it to plan, execute, and refine complex tasks across dynamic environments.

Trained for production-grade performance, M2.7 handles workflows such as live debugging, root cause analysis, financial modeling, and full document generation across Word, Excel, and PowerPoint. It delivers strong results on benchmarks including 56.2% on SWE-Pro and 57.0% on Terminal Bench 2, while achieving a 1495 ELO on GDPval-AA, setting a new standard for multi-agent systems operating in real-world digital workflows.

Modalities
In / Out Price
30% off
$0.21 / $0.84per 1M
Context
205K
Released
Mar 18, 2026
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ProvidersPricingPerformanceUptimeBenchmarksAppsActivityFAQExplore

Providers

Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick — Balanced (price + speed), Nitro (fastest), Floor (cheapest), or Exacto (highest tool-calling accuracy).

Pricing

The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.

Performance

Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Benchmarks

Scores on standardized evaluations and this model’s own outputs on shared benchmark prompts. Higher percentages are better — and each rank shows where this model lands among the models evaluated on that source.

Benchmark score summary for MiniMax: MiniMax M2.7 (Artificial Analysis, Design Arena and Vals AI)
SourceBenchmarkScore
Artificial AnalysisMiniMax-M2.7 Intelligence Index22.8
Artificial AnalysisMiniMax-M2.7 Coding Index52.6
Artificial AnalysisMiniMax-M2.7 Agentic Index15.3
Artificial AnalysisMiniMax-M2.7 GPQA Diamond87.4%
Artificial AnalysisMiniMax-M2.7 HLE29.6%
Artificial AnalysisMiniMax-M2.7 IFBench75.7%
Artificial AnalysisMiniMax-M2.7 τ²-Bench Telecom84.8%
Artificial AnalysisMiniMax-M2.7 AA-LCR78.3%
Artificial AnalysisMiniMax-M2.7 τ-Bench Banking9.9%
Artificial AnalysisMiniMax-M2.7 GDPval-AA25.7%
Artificial AnalysisMiniMax-M2.7 CritPt0.6%
Artificial AnalysisMiniMax-M2.7 SciCode50.1%
Artificial AnalysisMiniMax-M2.7 Terminal-Bench Hard39.4%
Artificial AnalysisMiniMax-M2.7 Terminal-Bench 4.00.0%
Artificial AnalysisMiniMax-M2.7 Terminal-Bench 2.155.4%
Artificial AnalysisMiniMax-M2.7 AA-Omniscience Accuracy26.8%
Artificial AnalysisMiniMax-M2.7 AA-Omniscience Non-Hallucination Rate64.4%
Design ArenaMiniMax M2.7 Models Arena 3D Elo1209
Design ArenaMiniMax M2.7 Models Arena Asciiart Elo1148
Design ArenaMiniMax M2.7 Models Arena Code Categories Elo1239
Design ArenaMiniMax M2.7 Models Arena Data Visualization Elo1242
Design ArenaMiniMax M2.7 Models Arena Game Development Elo1223
Design ArenaMiniMax M2.7 Models Arena SVG Elo1136
Design ArenaMiniMax M2.7 Models Arena UI Component Elo1216
Design ArenaMiniMax M2.7 Models Arena Website Elo1249
Vals AIMiniMax-M2.7 AIME91.0%
Vals AIMiniMax-M2.7 CaseLaw v260.9%
Vals AIMiniMax-M2.7 Code Migration8.7%
Vals AIMiniMax-M2.7 CorpFin v261.2%
Vals AIMiniMax-M2.7 EMB28.5%
Vals AIMiniMax-M2.7 Finance Agent (v2)27.9%
Vals AIMiniMax-M2.7 GPQA Diamond86.6%
Vals AIMiniMax-M2.7 Harvey's Legal Agent Benchmark0.0%
Vals AIMiniMax-M2.7 IOI v14.9%
Vals AIMiniMax-M2.7 LiveCodeBench79.9%
Vals AIMiniMax-M2.7 LegalBench84.0%
Vals AIMiniMax-M2.7 Legal Research Bench10.6%
Vals AIMiniMax-M2.7 MedCode34.4%
Vals AIMiniMax-M2.7 MedScribe79.9%
Vals AIMiniMax-M2.7 MMLU Pro80.4%
Vals AIMiniMax-M2.7 ProgramBench0.0%
Vals AIMiniMax-M2.7 ProofBench v13.0%
Vals AIMiniMax-M2.7 SWE-bench73.8%
Vals AIMiniMax-M2.7 Tax Agent Bench25.4%
Vals AIMiniMax-M2.7 TaxEval v266.6%
Vals AIMiniMax-M2.7 Terminal-Bench 2.148.7%
Vals AIMiniMax-M2.7 Vals Index41.6%
Vals AIMiniMax-M2.7 Vibe Code Bench v1.111.9%

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

Activity

Token volume and request traffic to this model over time.

API

Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.

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Frequently asked questions

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 collaboration, enabling it to plan, execute, and refine complex tasks across dynamic environments.

MiniMax M2.7 costs $0.21/M input tokens and $0.84/M output tokens, with separate rates for Cache Read at $0.042/M tokens.

MiniMax M2.7 has a 204,800 token context window.

Yes. MiniMax M2.7 accepts tools and tool_choice for function calling. It supports response_format for JSON output, without JSON-schema enforcement.

MiniMax M2.7 is served by 6 providers on OpenRouter: GMICloud, NovitaAI, AtlasCloud, MiniMax Highspeed, Groq, and SambaNova. Requests are routed to the best available provider, with automatic failover to the others, and you can pin or exclude providers with provider routing.

MiniMax M2.7 was released on March 18, 2026.