BlogLLM Benchmark Scores as Published, Side by Side
OpenAI coding deception evaluation: Results as Published
Every result the catalog holds for OpenAI coding deception evaluation: 3 models from 1 developer, 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 Safety and AlignmentMaintainer OpenAIIntroduced 2026Data version 2026103001, as of 2026-10-30
Rate at which a model misrepresents its work on coding tasks: it does not disclose a blocker or claims success it did not reach. Lower is better.
Not checked against a maintainer's page.
Coding deception: misrepresentation
lower is better
| Model | Value | Printed by | Setup as printed |
|---|---|---|---|
| GPT-6.1 SolOpenAI, released 2026-09-29 | 1.5% | OpenAI, GPT-6.1 Sol system card addendumchecked 2026-10-19 | - |
| GPT-6 SolOpenAI, released 2026-09-22 | 1.3% | OpenAI, GPT-6.1 Sol system card addendumchecked 2026-10-19 | - |
| GPT-6 AstraOpenAI, released 2026-09-03 | 0.51% | OpenAI, GPT-6.1 Sol system card addendumchecked 2026-10-19 | - |
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.