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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.
Quality Index
49.6
9th of 442
Top 2%
Coding Index
41.9
22nd of 352
Top 6%
Price/1M
$0.53
392nd cheapest
69% above median
Top 58%
Speed
44 tok/s
Top 52%
TTFT
1.82s
Context Window
205K
103rd largest
Top 30%
Input
$0.30
per 1M tokens
Output
$1.20
per 1M tokens
Blended
$0.53
per 1M tokens
Cheaper than 42% of models. Median price is $0.31/1M tokens.
Daily
$0.53
Monthly
$15.75
44
tokens/sec
Faster than 48% of models
1.82
seconds
Faster than 14% of models
47.80
seconds
Faster than 4% of models
Market Median
46 tok/s
5% slower
Median TTFT
0.42s
337% slower
Throughput/Dollar
83
tok/s per $/1M
Speed Comparison
Context Window
205K
tokens
Larger than 70% of models
Max Output
131K
tokens
64% of context