BlogLLM Benchmark Scores as Published, Side by Side
OpenAI instruction hierarchy robustness: Results as Published
Every result the catalog holds for OpenAI instruction hierarchy robustness: 4 models from 1 developer, read from 3 pages. Each number is as printed by the company named beside it; nothing is ranked or rescored. Models are listed by developer, newest first.
Area Safety and AlignmentMaintainer OpenAIIntroduced 2026Data version 2026103001, as of 2026-10-30
Robustness of the model to attacks that try to override higher-priority system or developer instructions with lower-priority user text, reported as one robustness percentage per model.
Not checked against a maintainer's page.
Instruction hierarchy robustness
| Model | Value | Printed by | Setup as printed |
|---|---|---|---|
| GPT-6.1 SolOpenAI, released 2026-09-29 | 99.99% | OpenAI, GPT-6.1 Sol system card addendumchecked 2026-10-19 | - |
| GPT-6 LunaOpenAI, released 2026-09-22 | 99.97% | OpenAI, GPT-6.1 Sol system card addendumchecked 2026-10-19; printed on 2 more pages | - |
| GPT-6 SolOpenAI, released 2026-09-22 | 99.99% | OpenAI, GPT-6 Sol and GPT-6 Luna: October 2026 updatechecked 2026-10-19; printed on 2 more pages | - |
| GPT-6 AstraOpenAI, released 2026-09-03 | 99.99% | OpenAI, GPT-6 Astra System Cardchecked 2026-10-25; printed on 1 more page | - |
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.