GPT-5.5 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-5.5 and MiniMax M2.7.
GPT-5.5
GPT-5.5 is OpenAI’s frontier model designed for complex professional workloads, building on GPT-5.4 with stronger reasoning, higher reliability, and improved token efficiency on hard tasks. It features a 1M+ token...
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-5.5 | MiniMax M2.7 |
|---|---|---|
| Provider | OpenAI | MiniMax |
| Context Window | 1,050,000 tokens | 204,800 tokens |
| Agent Suitability | 95/100 | N/A |
| Time to First Token (TTFT) | 380 ms | N/A |
| Deployment Model | managed api | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2026-04-24 | 2026-03-18 |
API Pricing Comparison
Input Price per Million Tokens
GPT-5.5
$5.00
MiniMax M2.7
$0.18
Output Price per Million Tokens
GPT-5.5
$30.00
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-5.5 Quirks & Gotchas
- ▸Best for JSON schema adherence — strict mode available via response_format parameter
- ▸Requires explicit tool_choice for deterministic function calling
MiniMax M2.7 Quirks & Gotchas
No developer gotchas reported.