Gemini 3.1 Pro 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 Gemini 3.1 Pro and MiniMax M2.7.
Gemini 3.1 Pro
Google's premiere multi-modal model featuring a massive 2 million token context window. Engineered for deep code analysis, video indexing, and long-context reasoning.
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 | Gemini 3.1 Pro | MiniMax M2.7 |
|---|---|---|
| Provider | MiniMax | |
| Context Window | 2,000,000 tokens | 204,800 tokens |
| Agent Suitability | 93/100 | N/A |
| Time to First Token (TTFT) | 420 ms | N/A |
| Deployment Model | managed api | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2026-04-20 | 2026-03-18 |
API Pricing Comparison
Input Price per Million Tokens
Gemini 3.1 Pro
$2.00
MiniMax M2.7
$0.18
Output Price per Million Tokens
Gemini 3.1 Pro
$12.00
MiniMax M2.7
$0.72
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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.
Gemini 3.1 Pro Quirks & Gotchas
- ▸Best model for massive context — 2M token window is class-leading
- ▸Tool calling requires explicit schema definition in Google AI Studio
MiniMax M2.7 Quirks & Gotchas
No developer gotchas reported.