M

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 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.

Input / 1M tokens
$0.300
Output / 1M tokens
$1.20
Context window
197K tokens
Provider
Minimax
Cached input / 1M
$0.059

Performance

Median streaming throughput and first-token latency measured by Artificial Analysis.

Output tokens / sec
44 t/s
Time to first token
1.46s

Benchmarks

Intelligence, coding, and math indexes plus the underlying evaluation scores.

Intelligence Index
50
Coding Index
42
Math Index
MMLU-Pro
GPQA
87.4%
HLE
28.1%
LiveCodeBench
SciCode
47.0%
MATH-500
AIME

Benchmarks via Artificial Analysis