BlogLLM Benchmark Scores as Published, Side by Side

Cybench: Results as Published

Every result the catalog holds for Cybench: 5 models from 4 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 Andy K. Zhang and co-authors (Stanford CRFM)Introduced 2024Data version 2026103001, as of 2026-10-30

Cybench gives a language-model agent 40 professional capture-the-flag tasks drawn from four distinct competitions chosen to be recent and to span a wide range of difficulty. Each task has its own description and starter files, and it starts in an environment where the agent can run commands and see the output. A task is solved when the answer the agent submits matches the answer key. Subtasks break a task into intermediate steps and are scored separately from fully unguided solutions.

Cybench

ModelValuePrinted bySetup as printed
DeepSeek-V4-Pro-0813DeepSeek88%Mistral AI, Mistral Large 4 (preview)checked 2026-10-15-
Kimi K3Moonshot AI, released 2026-07-1690%Mistral AI, Mistral Large 4 (preview)checked 2026-10-15-
GLM-5.3Z.ai, released 2026-08-1885%Mistral AI, Mistral Large 4 (preview)checked 2026-10-15-
GLM-5.2Z.ai, released 2026-06-1673%Mistral AI, Mistral Large 4 (preview)checked 2026-10-15-
Mistral Large 4 (preview)Mistral AI, released 2026-10-0693%Mistral 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.