BlogLLM Benchmark Scores as Published, Side by Side
SecCodeBench: Results as Published
Every result the catalog holds for SecCodeBench: 6 models from 5 developers, read from 1 page. Each number is as printed by the company named beside it; nothing is ranked or rescored. Models are listed by developer, newest first.
Area CybersecurityMaintainer Alibaba Group, with Tsinghua University, Zhejiang University, Fudan University, and Peking UniversityIntroduced 2026Data version 2026103001, as of 2026-10-30
SecCodeBench tests whether code from a model or a coding agent is both functional and secure. It has 98 runnable project tasks drawn from real vulnerabilities, in Java, C and C++, Python, Go, and Node.js, covering 22 CWE types, in both code generation and code repair. Code must pass the functional tests before any security check. Security is checked first by running an exploit, and otherwise by a judge model, and the published score is a weighted pass@1 that gives more weight to the setting with no security hint and to more severe weaknesses.
SecCodeBench
| Model | Value | Printed by | Setup as printed |
|---|---|---|---|
| GPT-5.2OpenAI, released 2025-12-11 | 68.7% | Alibaba, Qwen3.5-397B-A17B model cardchecked 2026-10-15 | - |
| Claude Opus 4.5Anthropic, released 2025-11-24 | 68.6% | Alibaba, Qwen3.5-397B-A17B model cardchecked 2026-10-15 | - |
| Gemini 3 ProGoogle, released 2025-11-18 | 62.4% | Alibaba, Qwen3.5-397B-A17B model cardchecked 2026-10-15 | - |
| Qwen3.5-397B-A17BAlibaba, released 2026-02-16 | 68.3% | Alibaba, Qwen3.5-397B-A17B model cardchecked 2026-10-15 | - |
| Qwen3-Max-ThinkingAlibaba | 57.5% | Alibaba, Qwen3.5-397B-A17B model cardchecked 2026-10-15 | - |
| Kimi K2.5Moonshot AI, released 2026-01-27 | 61.3% | Alibaba, Qwen3.5-397B-A17B model cardchecked 2026-10-15 | - |
Every number here is read from the same catalog file as the benchmark table, data version 2026103001, and is the number the table shows for that model and test. Where one page printed a model under several setups, each value is listed. The catalog is public in armanobosyan/sugra-llm-benchmarks; a wrong number can be reported from the table, with Report an error under the value, or as an issue in that repository.