GPT-4o-mini vs MiniMax M2.1
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-4o-mini and MiniMax M2.1.
GPT-4o-mini
GPT-4o mini is OpenAI's newest model after [GPT-4 Omni](/models/openai/gpt-4o), supporting both text and image inputs with text outputs. As their most advanced small model, it is many multiples more affordable...
MiniMax M2.1
MiniMax-M2.1 is a lightweight, state-of-the-art large language model optimized for coding, agentic workflows, and modern application development. With only 10 billion activated parameters, it delivers a major jump in real-world...
Technical Specifications
| Specification | GPT-4o-mini | MiniMax M2.1 |
|---|---|---|
| Provider | OpenAI | MiniMax |
| Context Window | 128,000 tokens | 204,800 tokens |
| Agent Suitability | 82/100 | N/A |
| Time to First Token (TTFT) | 150 ms | N/A |
| Deployment Model | managed api | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2024-07-18 | 2025-12-23 |
API Pricing Comparison
Input Price per Million Tokens
GPT-4o-mini
$0.15
MiniMax M2.1
$0.30
Output Price per Million Tokens
GPT-4o-mini
$0.60
MiniMax M2.1
$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-4o-mini Quirks & Gotchas
- ▸Ultra-low latency — best TTFT in the OpenAI lineup
- ▸Tool calling limited to single-step — not suitable for complex agentic pipelines
MiniMax M2.1 Quirks & Gotchas
No developer gotchas reported.