MiniMax M1 vs o3 Mini
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 MiniMax M1 and o3 Mini.
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...
o3 Mini
OpenAI o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and coding. This model supports the `reasoning_effort` parameter, which can be set to...
Technical Specifications
| Specification | MiniMax M1 | o3 Mini |
|---|---|---|
| Provider | MiniMax | OpenAI |
| Context Window | 1,000,000 tokens | 200,000 tokens |
| Agent Suitability | N/A | 91/100 |
| Time to First Token (TTFT) | N/A | 800 ms |
| Deployment Model | managed api | managed api |
| Production Stability | beta | stable |
| API Available | Yes | Yes |
| Released Date | 2025-06-17 | 2025-01-31 |
API Pricing Comparison
Input Price per Million Tokens
MiniMax M1
$0.40
o3 Mini
$1.10
Output Price per Million Tokens
MiniMax M1
$2.20
o3 Mini
$4.40
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.
MiniMax M1 Quirks & Gotchas
No developer gotchas reported.
o3 Mini Quirks & Gotchas
- ▸Best cost/performance ratio for reasoning tasks in the OpenAI lineup
- ▸Still slower than GPT-5 for simple tool calls — route accordingly