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code benchmark

SecCodeBench Leaderboard

SecCodeBench evaluates LLM coding agents on secure code generation and vulnerability detection.

Updated Sep 5, 2026

Models1
Model coverage1
MetricScore
EvidenceB

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  • FAQ

SecCodeBench Ranking

Higher score ranks better on this benchmark.

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Rank
Model
Score
Percentile
Participants
Evidence
Evaluated
Rank01ModelACQwen3.5-397B-A17BAlibaba Cloud / Qwen TeamScore68.30%Percentile100.00%Participants1EvidenceCEvaluatedSep 8, 2026

SecCodeBench Highlights

The leading models and scores on this benchmark.

Rank #1Qwen3.5-397B-A17B68.30%

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.

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.

  1. 01
    AC
    Alibaba Cloud / Qwen Team
    Score
    68.30%
    Price
    $0.60 input / $3.6 output per 1M tokens

    Strengths

    • Ranks #1 of 1 compared models
    • 100th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures SecCodeBench, not total model capability

Selection summary

Best AI Models for SecCodeBench

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 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%).

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.

What does SecCodeBench measure?

It measures secure code generation and vulnerability detection, including the ability to produce functional code that is free from security vulnerabilities.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

1 model results are currently shown.

Does this benchmark affect the overall score?

No. This benchmark is shown for reference but does not contribute to the overall score.

Qwen3.5-397B-A17B
Benchmark rank #1Qwen3.5-397B-A17B68.30% · $0.60 input / $3.6 output per 1M tokens