SecCodeBench
SecCodeBench evaluates LLM coding agents on secure code generation and vulnerability detection, testing the ability to produce code that is both functional and free from security vulnerabilities.
Progress Over Time
Interactive timeline showing model performance evolution on SecCodeBench
State-of-the-art frontier
Open
Proprietary
SecCodeBench Leaderboard
1 models
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 |  Alibaba Cloud / Qwen Team | 397B | 262K | $0.60 / $3.60 |
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FAQ
Common questions about SecCodeBench
SecCodeBench evaluates LLM coding agents on secure code generation and vulnerability detection, testing the ability to produce code that is both functional and free from security vulnerabilities.
The SecCodeBench leaderboard ranks 1 AI models based on their performance on this benchmark. Currently, Qwen3.5-397B-A17B by Alibaba Cloud / Qwen Team leads with a score of 0.683. The average score across all models is 0.683.
The highest SecCodeBench score is 0.683, achieved by Qwen3.5-397B-A17B from Alibaba Cloud / Qwen Team.
1 models have been evaluated on the SecCodeBench benchmark, with 0 verified results and 1 self-reported results.
SecCodeBench is categorized under coding. The benchmark evaluates text models.