DeepSeek-V3.2-Exp
Zero-eval
#1SimpleQA
#1MMLU-Pro
#1SWE-bench Multilingual
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by DeepSeek
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About
DeepSeek-V3.2-Exp is a language model developed by DeepSeek. It achieves strong performance with an average score of 66.1% across 14 benchmarks. It excels particularly in SimpleQA (97.1%), AIME 2025 (89.3%), MMLU-Pro (85.0%). It supports a 229K token context window for handling large documents. The model is available through 2 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents DeepSeek's latest advancement in AI technology.
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Pricing Range
Input (per 1M)$0.27 -$0.27
Output (per 1M)$0.41 -$0.41
Providers2
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Timeline
AnnouncedSep 29, 2025
ReleasedSep 29, 2025
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License & Family
License
MIT
Performance Overview
Performance metrics and category breakdown
Overall Performance
14 benchmarks
Average Score
66.1%
Best Score
97.1%
High Performers (80%+)
4Performance Metrics
Max Context Window
229.4KAvg Throughput
100.0 tok/sAvg Latency
1ms+
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All Benchmark Results for DeepSeek-V3.2-Exp
Complete list of benchmark scores with detailed information
| SimpleQA | text | 0.97 | 97.1% | Self-reported | |
| AIME 2025 | text | 0.89 | 89.3% | Self-reported | |
| MMLU-Pro | text | 0.85 | 85.0% | Self-reported | |
| HMMT 2025 | text | 0.84 | 83.6% | Self-reported | |
| GPQA | text | 0.80 | 79.9% | Self-reported | |
| Aider-Polyglot | text | 0.74 | 74.5% | Self-reported | |
| LiveCodeBench | text | 0.74 | 74.1% | Self-reported | |
| CodeForces | text | 0.71 | 70.7% | Self-reported | |
| SWE-Bench Verified | text | 0.68 | 67.8% | Self-reported | |
| SWE-bench Multilingual | text | 0.58 | 57.9% | Self-reported |
Showing 1 to 10 of 14 benchmarks