GPT-5.5 vs MiniMax M2-her
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-her.
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-her
MiniMax M2-her is a dialogue-first large language model built for immersive roleplay, character-driven chat, and expressive multi-turn conversations. Designed to stay consistent in tone and personality, it supports rich message...
Technical Specifications
| Specification | GPT-5.5 | MiniMax M2-her |
|---|---|---|
| Provider | OpenAI | MiniMax |
| Context Window | 1,050,000 tokens | 65,536 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 | 2026-01-23 |
API Pricing Comparison
Input Price per Million Tokens
GPT-5.5
$5.00
MiniMax M2-her
$0.30
Output Price per Million Tokens
GPT-5.5
$30.00
MiniMax M2-her
$1.20
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.
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-her Quirks & Gotchas
No developer gotchas reported.