MiniMax: MiniMax M2.7
MiniMax • LLM
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...
Specifications
Context Window
197K tokens
Input Price/1M
$0.30
Output Price/1M
$1.20
Parameters
—
Speed
107 tok/s
Latency (TTFT)
1.1s
Benchmarks
MiniMax: MiniMax M2.7 results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
Agentic
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| Terminal-Bench Hard | 39.0 | 100.0 | — |
Coding
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| LiveCodeBench | 83.0 | 100.0 | — |
| SciCode | 47.0 | 100.0 | — |
| AA Coding Index | 41.9 | 100.0 | Artificial Analysis official API |
Knowledge
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MMLU-Pro | 82.0 | 100.0 | — |
Long Context
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA-LCR | 69.0 | 100.0 | — |
Math
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Math Index | 78.3 | 100.0 | — |
| AIME 2025 | 78.0 | 100.0 | — |
overall
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Intelligence Index | 49.6 | 100.0 | Artificial Analysis official API |
Reasoning
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| GPQA Diamond | 87.0 | 100.0 | Artificial Analysis official API |
| IFBench | 76.0 | 100.0 | — |
| HLE | 28.0 | 100.0 | — |
Tool Use
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| Tau²-Bench | 87.0 | 100.0 | — |
Information
- Release date
- October 26, 2025
- Tool Calling
- ✅ Supported
- Vision
- ❌ Not supported
- Audio
- ❌ Not supported
Full Analysis: MiniMax: MiniMax M2.7
What is MiniMax: MiniMax M2.7?
MiniMax: MiniMax M2.7 is an AI model developed by MiniMax, classified as a large language model (LLM). It focuses on text processing and natural language generation. As an open source model, it is available for download, customization, and on-premises deployment. With a context window of 197K tokens, it is suitable for processing long documents such as contracts, books, and complete codebases.
Pricing & Costs in 2026
MiniMax: MiniMax M2.7 is usage-based, priced at $0.3/1M input tokens and $1.2/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. At this aggressive price point, it is one of the most cost-effective options on the market, ideal for high-volume applications like chatbots, bulk document analysis, and automation.
Benchmarks & Performance
MiniMax: MiniMax M2.7 was evaluated on 13 different benchmarks, covering categories like Agentic, Coding, Knowledge, Long Context, Math, overall, Reasoning, Tool Use. Results show solid performance across available evaluations.
It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.
Recommended Use Cases
MiniMax: MiniMax M2.7 is suitable for a wide range of AI applications: long document analysis (contracts, legal proceedings, codebases), automation with tool calling (API integration, databases, external systems), high-volume chatbots and automated support, complex reasoning, math problem solving, and logical analysis, text generation, summarization, translation, and general assistance.
Comparison with Alternatives
In the 2026 AI model ecosystem, MiniMax: MiniMax M2.7 competes directly with similarly capable models. MiniMax competes in this segment against OpenAI, Anthropic, Google, and Meta. The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.
For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.
Frequently Asked Questions
What is 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...
How much does MiniMax: MiniMax M2.7 cost?
MiniMax: MiniMax M2.7 costs $0.3/1M input tokens and $1.2/1M output tokens. For heavy usage (e.g., a chatbot handling 100k messages/month), costs can range from $10 to $1,000 depending on volume.
How does MiniMax: MiniMax M2.7 compare with other models?
In available benchmarks, MiniMax: MiniMax M2.7 scored: Terminal-Bench Hard: 39/100, LiveCodeBench: 83/100, SciCode: 47/100. See the full table above for a detailed comparison.
Is MiniMax: MiniMax M2.7 open source?
Yes, MiniMax: MiniMax M2.7 is an open source model. You can deploy it on-premises, customize it via fine-tuning, and maintain full control over your data. Check the official repository for the specific license.
What is MiniMax: MiniMax M2.7 best for?
MiniMax: MiniMax M2.7 excels at complex reasoning and problem solving. With its large context window, it handles long documents, codebases, and extended conversations. It supports tool calling for API integrations and automation.
Last updated: June 01, 2026 • View methodology →