GPT-4.1 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 GPT-4.1 and MiniMax M2.7.
GPT-4.1
GPT-4.1 is a flagship large language model optimized for advanced instruction following, real-world software engineering, and long-context reasoning. It supports a 1 million token context window and outperforms GPT-4o and...
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 | GPT-4.1 | MiniMax M2.7 |
|---|---|---|
| Provider | OpenAI | MiniMax |
| Context Window | 1,047,576 tokens | 204,800 tokens |
| Agent Suitability | 91/100 | N/A |
| Time to First Token (TTFT) | 250 ms | N/A |
| Deployment Model | managed api | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2025-04-14 | 2026-03-18 |
API Pricing Comparison
Input Price per Million Tokens
GPT-4.1
$2.00
MiniMax M2.7
$0.18
Output Price per Million Tokens
GPT-4.1
$8.00
MiniMax M2.7
$0.72
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.
GPT-4.1 Quirks & Gotchas
- ▸Strong tool-calling reliability — good migration path from GPT-4o
- ▸Migrate to GPT-5 for larger context window and improved reasoning
MiniMax M2.7 Quirks & Gotchas
No developer gotchas reported.