GPT-5 Mini 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 GPT-5 Mini and MiniMax M1.
GPT-5 Mini
GPT-5 Mini is a compact version of GPT-5, designed to handle lighter-weight reasoning tasks. It provides the same instruction-following and safety-tuning benefits as GPT-5, but with reduced latency and cost....
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 | GPT-5 Mini | MiniMax M1 |
|---|---|---|
| Provider | OpenAI | MiniMax |
| Context Window | 400,000 tokens | 1,000,000 tokens |
| Agent Suitability | 85/100 | N/A |
| Time to First Token (TTFT) | 180 ms | N/A |
| Deployment Model | managed api | managed api |
| Production Stability | stable | beta |
| API Available | Yes | Yes |
| Released Date | 2025-08-07 | 2025-06-17 |
API Pricing Comparison
Input Price per Million Tokens
GPT-5 Mini
$0.25
MiniMax M1
$0.40
Output Price per Million Tokens
GPT-5 Mini
$2.00
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.
GPT-5 Mini Quirks & Gotchas
- ▸Excellent for high-frequency classification and routing tasks
- ▸Tool calling reliability drops on complex multi-step chains — use GPT-5 for agentic workflows
MiniMax M1 Quirks & Gotchas
No developer gotchas reported.