code benchmark
SecCodeBench Leaderboard
SecCodeBench evaluates LLM coding agents on secure code generation and vulnerability detection.
Updated Oct 23, 2026
Models2
Model coverage2
MetricScore
EvidenceB
SecCodeBench Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelAC | Score68.30% | Percentile100.00% | Participants2 | EvidenceC | Evaluated |
| Rank02 | ModelAC | Score57.50% | Percentile0.00% | Participants2 | EvidenceC | Evaluated |
SecCodeBench Highlights
The leading models and scores on this benchmark.
SecCodeBench Score Distribution
A closer view of the leading scores on this benchmark.
The Top AI Models for SecCodeBench
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
What is SecCodeBench?
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.
- Family
- SecCodeBench
- Modality
- text
- Primary category
- code
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- overall
LLM Stats. Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about SecCodeBench.
Which model scores highest on SecCodeBench?
Qwen3.5-397B-A17B is currently ranked first with 68.30%.
What are the top three models on SecCodeBench?
The current leaders are Qwen3.5-397B-A17B (68.30%) and Qwen3 Max Thinking (57.50%).
Which SecCodeBench model has the lowest official input price?
Qwen3.5-397B-A17B has the lowest matched official input price at $0.60 input / $3.6 output per 1M tokens.
Which models are fastest among SecCodeBench results?
No matched runtime record is currently available.
Does the highest score result prove overall model quality?
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.