MiniMax M2.7 vs o4 Mini Deep Research
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 M2.7 and o4 Mini Deep Research.
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...
o4 Mini Deep Research
o4-mini-deep-research is OpenAI's faster, more affordable deep research model—ideal for tackling complex, multi-step research tasks. Note: This model always uses the 'web_search' tool which adds additional cost.
Technical Specifications
| Specification | MiniMax M2.7 | o4 Mini Deep Research |
|---|---|---|
| Provider | MiniMax | OpenAI |
| Context Window | 204,800 tokens | 200,000 tokens |
| Agent Suitability | N/A | N/A |
| Time to First Token (TTFT) | N/A | N/A |
| Deployment Model | managed api | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2026-03-18 | 2025-10-10 |
API Pricing Comparison
Input Price per Million Tokens
MiniMax M2.7
$0.18
o4 Mini Deep Research
$2.00
Output Price per Million Tokens
MiniMax M2.7
$0.72
o4 Mini Deep Research
$8.00
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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 M2.7 Quirks & Gotchas
No developer gotchas reported.
o4 Mini Deep Research Quirks & Gotchas
No developer gotchas reported.