DeepSeek-V3.1 vs MiniMax M2.1: Specs & Benchmark Comparison
| Characteristic | DeepSeek-V3.1 | MiniMax M2.1 |
|---|---|---|
| Company | DeepSeek | MiniMax |
| Release Date | January 9, 2025 | December 22, 2025 |
| Parameters | 671B | — |
| Multimodal | No | No |
| Context (input) | 164K | 1.0M |
| Context (output) | 164K | 100K |
| Input Price / 1M | $0.27 | $0.30 |
| Output Price / 1M | $1.00 | $1.20 |
| Average Score | 0.8 | 0.9 |
| Benchmarks | ||
| GPQA | 0.8 | 0.8 |
| MMLU-Pro | 0.8 | 0.9 |
Visual Benchmark Comparison
DeepSeek-V3.1
MiniMax M2.1
GPQA0.8 vs 0.8
0.8
0.8
MMLU-Pro0.8 vs 0.9
0.8
0.9
Verdict
MiniMax M2.1 leads in 2 out of 4 comparison categories.
Overall Performance
Both models show comparable average scores: DeepSeek-V3.1 — 0.8, MiniMax M2.1 — 0.9.
API Cost
DeepSeek-V3.1 is 1.2x cheaper: input $0.27/1M vs $0.30/1M tokens.
Context Window
MiniMax M2.1 supports a larger context: 1M vs 164K tokens.
Recency
MiniMax M2.1 is newer: released 12/22/2025 vs 1/9/2025.
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Frequently Asked Questions
Which is better for coding — DeepSeek-V3.1 or MiniMax M2.1?
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 M2.1?
DeepSeek-V3.1 is cheaper for input: $0.27 per 1M tokens vs $0.30.
Which has a larger context window — DeepSeek-V3.1 or MiniMax M2.1?
MiniMax M2.1 supports a larger context: 1,000,000 tokens vs 163,840.
The DeepSeek-V3.1 and MiniMax M2.1 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 M2.1 page. See also the complete list of AI model comparisons.