MiniMax M1 vs MiniMax M2.7
How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for MiniMax M1 and MiniMax M2.7.
MiniMax M1
MiniMax-M1 is a large-scale, open-weight reasoning model designed for extended context and high-efficiency inference. It leverages a hybrid Mixture-of-Experts (MoE) architecture paired with a custom "lightning attention" mechanism, allowing it...
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...
Technical Specifications
| Specification | MiniMax M1 | MiniMax M2.7 |
|---|---|---|
| Provider | MiniMax | MiniMax |
| Context Window | 1,000,000 tokens | 204,800 tokens |
| Agent Suitability | N/A | N/A |
| Time to First Token (TTFT) | N/A | N/A |
| Deployment Model | managed api | managed api |
| Production Stability | beta | stable |
| API Available | Yes | Yes |
| Released Date | 2025-06-17 | 2026-03-18 |
API Pricing Comparison
Input Price per Million Tokens
MiniMax M1
$0.40
MiniMax M2.7
$0.18
Output Price per Million Tokens
MiniMax M1
$2.20
MiniMax M2.7
$0.72
Want to test both models live?
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Benchmark Performance Metrics
Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.
MiniMax M1 Quirks & Gotchas
No developer gotchas reported.
MiniMax M2.7 Quirks & Gotchas
No developer gotchas reported.