DeepSeek-V3.1 vs MiniMax M2: Specs & Benchmark Comparison
| Characteristic | DeepSeek-V3.1 | MiniMax M2 |
|---|---|---|
| Company | DeepSeek | MiniMax |
| Release Date | January 9, 2025 | October 26, 2025 |
| Parameters | 671B | 230B |
| Multimodal | No | No |
| Context (input) | 164K | 1.0M |
| Context (output) | 164K | 100K |
| Input Price / 1M | $0.27 | $1.00 |
| Output Price / 1M | $1.00 | $4.00 |
| Average Score | 0.8 | 0.8 |
| Benchmarks | ||
| GPQA | 0.8 | 0.8 |
| MMLU-Pro | 0.8 | 0.8 |
Visual Benchmark Comparison
DeepSeek-V3.1
MiniMax M2
GPQA0.8 vs 0.8
0.8
0.8
MMLU-Pro0.8 vs 0.8
0.8
0.8
Verdict
MiniMax M2 leads in 2 out of 4 comparison categories.
Overall Performance
Both models show comparable average scores: DeepSeek-V3.1 — 0.8, MiniMax M2 — 0.8.
API Cost
DeepSeek-V3.1 is 3.9x cheaper: input $0.27/1M vs $1.00/1M tokens.
Context Window
MiniMax M2 supports a larger context: 1M vs 164K tokens.
Recency
MiniMax M2 is newer: released 10/26/2025 vs 1/9/2025.
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Frequently Asked Questions
Which is better for coding — DeepSeek-V3.1 or MiniMax M2?
Direct comparison on the SWE-Bench benchmark is not available. We recommend reviewing other metrics on the comparison page.
Which model is cheaper — DeepSeek-V3.1 or MiniMax M2?
DeepSeek-V3.1 is cheaper for input: $0.27 per 1M tokens vs $1.00.
Which has a larger context window — DeepSeek-V3.1 or MiniMax M2?
MiniMax M2 supports a larger context: 1,000,000 tokens vs 163,840.
The DeepSeek-V3.1 and MiniMax M2 comparison is updated for 2026. Data includes benchmark results, API pricing, context window size and other specifications. For more detailed information, visit the DeepSeek-V3.1 or MiniMax M2 page. See also the complete list of AI model comparisons.