DeepSeek-V3.1 vs DeepSeek-V3.2 (Thinking): Specs & Benchmark Comparison
| Characteristic | DeepSeek-V3.1 | DeepSeek-V3.2 (Thinking) |
|---|---|---|
| Company | DeepSeek | DeepSeek |
| Release Date | January 9, 2025 | November 30, 2025 |
| Parameters | 671B | 685B |
| Multimodal | No | No |
| Context (input) | 164K | 131K |
| Context (output) | 164K | 66K |
| Input Price / 1M | $0.27 | $0.28 |
| Output Price / 1M | $1.00 | $0.42 |
| Average Score | 0.8 | 0.9 |
| Benchmarks | ||
| GPQA | 0.8 | 0.8 |
| MMLU-Pro | 0.8 | 0.8 |
Visual Benchmark Comparison
DeepSeek-V3.1
DeepSeek-V3.2 (Thinking)
GPQA0.8 vs 0.8
0.8
0.8
MMLU-Pro0.8 vs 0.8
0.8
0.8
Verdict
DeepSeek-V3.2 (Thinking) leads in 2 out of 4 comparison categories.
Overall Performance
Both models show comparable average scores: DeepSeek-V3.1 — 0.8, DeepSeek-V3.2 (Thinking) — 0.9.
API Cost
DeepSeek-V3.2 (Thinking) is 1.8x cheaper: input $0.28/1M vs $0.27/1M tokens.
Context Window
DeepSeek-V3.1 supports a larger context: 164K vs 131K tokens.
Recency
DeepSeek-V3.2 (Thinking) is newer: released 11/30/2025 vs 1/9/2025.
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Frequently Asked Questions
Which is better for coding — DeepSeek-V3.1 or DeepSeek-V3.2 (Thinking)?
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 DeepSeek-V3.2 (Thinking)?
DeepSeek-V3.1 is cheaper for input: $0.27 per 1M tokens vs $0.28.
Which has a larger context window — DeepSeek-V3.1 or DeepSeek-V3.2 (Thinking)?
DeepSeek-V3.1 supports a larger context: 163,840 tokens vs 131,072.
The DeepSeek-V3.1 and DeepSeek-V3.2 (Thinking) 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 DeepSeek-V3.2 (Thinking) page. See also the complete list of AI model comparisons.