code benchmark
SecCodeBench evaluates LLM coding agents on secure code generation and vulnerability detection.
Updated Sep 5, 2026
Higher score ranks better on this benchmark.
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelAC | Score68.30% | Percentile100.00% | Participants1 | EvidenceC | Evaluated |
The leading models and scores on this benchmark.
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis seccodebench AI model leaderboard uses descending score in the benchmark original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
Selection summary
Qwen3.5-397B-A17B currently leads SecCodeBench with 68.30%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price, and runtime.
Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.
What SecCodeBench measures and how its scores work.
SecCodeBench is a code benchmark for evaluating LLM coding agents.
It measures secure code generation and vulnerability detection, including the ability to produce functional code that is free from security vulnerabilities.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
LLM Stats. Benchmark scores retain their original unit. Overall score eligibility is shown separately.
Common questions about SecCodeBench.
Qwen3.5-397B-A17B is currently ranked first with 68.30%.
The current leaders are Qwen3.5-397B-A17B (68.30%).
Qwen3.5-397B-A17B has the lowest matched official input price at $0.60 input / $3.6 output per 1M tokens.
No matched runtime record is currently available.
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.
It measures secure code generation and vulnerability detection, including the ability to produce functional code that is free from security vulnerabilities.
Yes. Higher values rank better for this benchmark.
1 model results are currently shown.
No. This benchmark is shown for reference but does not contribute to the overall score.