BlogLLM Benchmark Scores as Published, Side by Side

Artificial Analysis Cyber Index: Results as Published

Every result the catalog holds for Artificial Analysis Cyber Index: 8 models from 7 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 Artificial AnalysisData version 2026103001, as of 2026-10-30

The Artificial Analysis Cyber Index measures defensive work on real software: finding vulnerabilities, reproducing and checking them, and patching them without breaking existing behavior. It does not ask a model to build a working exploit. The index is an equal average of three scores, CWE-Bench-AA pass@1, DeepsecBench-AA F2 (the median of three runs), and CyberGym-E2E-AA pass@1, each placed on a 0 to 100 scale. A task declined on safety grounds scores zero, and safety blocks are also reported as their own average across the three tests.

Artificial Analysis Cyber Index (successes)

ModelValuePrinted bySetup as printed
GPT-6 AstraOpenAI, released 2026-09-0333Mistral AI, Mistral Large 4 (preview)checked 2026-10-15-
Claude Opus 5.5Anthropic, released 2026-09-2229Mistral AI, Mistral Large 4 (preview)checked 2026-10-15-
DeepSeek-V4.1-FlashDeepSeek, released 2026-09-1041Mistral AI, Mistral Large 4 (preview)checked 2026-10-15-
Qwen3.8-2.4T-A95BAlibaba13Mistral AI, Mistral Large 4 (preview)checked 2026-10-15-
Kimi K3Moonshot AI, released 2026-07-1641Mistral AI, Mistral Large 4 (preview)checked 2026-10-15-
GLM-5.3-FlashZ.ai, released 2026-08-2650Mistral AI, Mistral Large 4 (preview)checked 2026-10-15-
GLM-5.3Z.ai, released 2026-08-1836Mistral AI, Mistral Large 4 (preview)checked 2026-10-15-
Mistral Large 4 (preview)Mistral AI, released 2026-10-0650Mistral AI, Mistral Large 4 (preview)checked 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.