DeepSeek-V3
Zero-eval
#1DROP
#1HumanEval-Mul
#1Aider-Polyglot Edit
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by DeepSeek
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About
DeepSeek-V3 is a language model developed by DeepSeek. It achieves strong performance with an average score of 67.2% across 20 benchmarks. It excels particularly in DROP (91.6%), CLUEWSC (90.9%), MATH-500 (90.2%). It supports a 262K token context window for handling large documents. The model is available through 1 API provider. Released in 2024, 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)$1.10 -$1.10
Providers1
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Timeline
AnnouncedDec 25, 2024
ReleasedDec 25, 2024
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Specifications
Training Tokens14.8T
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License & Family
License
MIT + Model License (Commercial use allowed)
Performance Overview
Performance metrics and category breakdown
Overall Performance
20 benchmarks
Average Score
67.2%
Best Score
91.6%
High Performers (80%+)
8Performance Metrics
Max Context Window
262.1KAvg Throughput
100.0 tok/sAvg Latency
1ms+
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All Benchmark Results for DeepSeek-V3
Complete list of benchmark scores with detailed information
| DROP | text | 0.92 | 91.6% | Self-reported | |
| CLUEWSC | text | 0.91 | 90.9% | Self-reported | |
| MATH-500 | text | 0.90 | 90.2% | Self-reported | |
| MMLU-Redux | text | 0.89 | 89.1% | Self-reported | |
| MMLU | text | 0.89 | 88.5% | Self-reported | |
| C-Eval | text | 0.86 | 86.5% | Self-reported | |
| IFEval | text | 0.86 | 86.1% | Self-reported | |
| HumanEval-Mul | text | 0.83 | 82.6% | Self-reported | |
| Aider-Polyglot Edit | text | 0.80 | 79.7% | Self-reported | |
| MMLU-Pro | text | 0.76 | 75.9% | Self-reported |
Showing 1 to 10 of 20 benchmarks