Minimax 2.7
About this model
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.
Performance Tier
Minimax 2.7 is a flagship model from Minimax : the most capable in their lineup.
Best-in-class model from this provider. Highest performance across benchmarks, ideal for demanding tasks.
Pricing
This model is included in Elosia plans| Type | per 1M tokens |
|---|---|
| Input (prompt) | $0.300 |
| Output (completion) | $1.20 |
| Cache read | $0.060 |
Capabilities
Benchmarks
Recommended Use Cases
Strengths
- Industry-leading agentic coding (SWE-Pro 56.2%, Terminal-Bench 57.0%)
- Full project delivery capability (VIBE-Pro 55.6%)
- Self-evolving model with autonomous research workflow capabilities
- Extremely cost-efficient at $0.30/$1.20 per M tokens with 205K context
Limitations
- No standard academic benchmarks published (MMLU, GPQA, MATH)
- Text-only — no multimodal support
- Smaller community and ecosystem compared to Claude/GPT/Gemini
Resources
This model may use your data for training
