Gemini 2.5 Pro vs MiniMax M1
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 M1.
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 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...
Technical Specifications
| Specification | Gemini 2.5 Pro | MiniMax M1 |
|---|---|---|
| Provider | MiniMax | |
| Context Window | 1,048,576 tokens | 1,000,000 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 | beta |
| API Available | Yes | Yes |
| Released Date | 2025-06-17 | 2025-06-17 |
API Pricing Comparison
Input Price per Million Tokens
Gemini 2.5 Pro
$1.25
MiniMax M1
$0.40
Output Price per Million Tokens
Gemini 2.5 Pro
$10.00
MiniMax M1
$2.20
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 M1 Quirks & Gotchas
No developer gotchas reported.