DeepSeek V3.2 vs MiniMax M2
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 DeepSeek V3.2 and MiniMax M2.
DeepSeek V3.2
DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...
MiniMax M2
MiniMax-M2 is a compact, high-efficiency large language model optimized for end-to-end coding and agentic workflows. With 10 billion activated parameters (230 billion total), it delivers near-frontier intelligence across general reasoning,...
Technical Specifications
| Specification | DeepSeek V3.2 | MiniMax M2 |
|---|---|---|
| Provider | DeepSeek | MiniMax |
| Context Window | 131,072 tokens | 204,800 tokens |
| Agent Suitability | N/A | N/A |
| Time to First Token (TTFT) | N/A | N/A |
| Deployment Model | self hostable | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2025-12-01 | 2025-10-23 |
API Pricing Comparison
Input Price per Million Tokens
DeepSeek V3.2
$0.23
MiniMax M2
$0.26
Output Price per Million Tokens
DeepSeek V3.2
$0.34
MiniMax M2
$1.02
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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.
DeepSeek V3.2 Quirks & Gotchas
No developer gotchas reported.
MiniMax M2 Quirks & Gotchas
No developer gotchas reported.