MiniMax M2.7
minimax-m2.7MiniMax-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... Built by MiniMax.
Prices updated
Input price
$0.21
per 1M tokens · Standard
Output price
$0.84
per 1M tokens · Standard
Input limit
205K
tokens
Output limit
177K
tokens
Input formats
Output formats
MiniMax M2.7 price history
4 price records since 9/25/2026 · 2 changes
MiniMax M2.7 cost calculator
$8.40/month
Standard pricing
Overview
What is MiniMax M2.7?
MiniMax M2.7 is a text & reasoning model from MiniMax. 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... Its 205K context window and $0.21 input price make it a candidate for cost-sensitive, high-throughput applications.
Benchmarks
MiniMax M2.7 benchmarks & speed
How MiniMax M2.7 scores on standardized evaluations, and where it lands among every model we track.
22.8
Intelligence Index
65tok/s
Output speed
Reasoning
GPQA Diamond
87.4%
Graduate-level scientific reasoning · top 34%
HLE
29.6%
Humanity's Last Exam · top 36%
Coding
SciCode
50.1%
Python for scientific computing · top 51%
Latency & design
- Time to first token
- 1.52s
Independent scores from Artificial Analysis and DesignArena · updated 10/5/2026. Higher is better; ranks compare against every model we track with that score.
Rates
MiniMax M2.7 pricing
Pricing is based on token usage. Provider-specific caching, batch, regional, and tool charges may affect the final cost.
Input · Standard
$0.21
Per 1M tokens
Cached input · Standard
$0.04
Per 1M tokens
Capabilities
MiniMax M2.7 Tools
Tools available when using MiniMax M2.7 through supported provider APIs.
Function calling
Supported
Structured outputs
Not supported
JSON mode
Supported
Reasoning
Supported
Built-in web search
Not supported
Log probabilities
Not supported
Deterministic seed
Supported
Parallel tool calls
Not supported
Prompt caching
Supported
Strengths and limitations
Strengths
- Low input cost at $0.21 per million tokens suits high-volume workloads.
- 205K context supports large documents, repositories and extended conversations.
- Supports text & reasoning workloads in one model.
Limitations
- Generated tokens cost 4× more than input tokens, which matters for verbose responses.
- Large context capacity does not guarantee consistent retrieval across the entire prompt.
- Arena Elo and MMLU-Pro are directional; test accuracy, latency and reliability on your own workload before committing.
Arena Elo, MMLU-Pro and pricing figures are illustrative; validate current vendor terms before purchase.
Same provider