Gemini 2.5 Pro vs MiniMax M2
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 2.5 Pro and MiniMax M2.
Gemini 2.5 Pro
Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy...
MiniMax M2
MiniMax-M2 is a compact, high-efficiency large language model optimized for end-to-end coding and agentic workflows. With 10 billion activated parameters (230 billion total), it delivers near-frontier intelligence across general reasoning,...
Technical Specifications
| Specification | Gemini 2.5 Pro | MiniMax M2 |
|---|---|---|
| Provider | MiniMax | |
| Context Window | 1,048,576 tokens | 204,800 tokens |
| Agent Suitability | 90/100 | N/A |
| Time to First Token (TTFT) | 450 ms | N/A |
| Deployment Model | managed api | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2025-06-17 | 2025-10-23 |
API Pricing Comparison
Input Price per Million Tokens
Gemini 2.5 Pro
$1.25
MiniMax M2
$0.26
Output Price per Million Tokens
Gemini 2.5 Pro
$10.00
MiniMax M2
$1.02
Want to test both models live?
Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.
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 2.5 Pro Quirks & Gotchas
- ▸Legacy model — migrate to Gemini 3.1 Pro for better tool calling and lower latency
MiniMax M2 Quirks & Gotchas
No developer gotchas reported.