BlogLLM Benchmark Scores as Published, Side by Side
OpenAI Internal Data Science Tasks: Results as Published
Every result the catalog holds for OpenAI Internal Data Science Tasks: 3 models from 2 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 ML EngineeringMaintainer OpenAI (internal evaluation)Data version 2026103001, as of 2026-10-30
OpenAI's GPT-6 Astra launch page lists an internal Data Science Tasks evaluation in its benchmark charts, printing a score for each model. The page does not describe the tasks, the inputs or the scoring, and it does not state which direction is better. By its name the evaluation covers data science work on a dataset, but OpenAI has not confirmed the details.
Not checked against a maintainer's page.
Internal Data Science Tasks
| Model | Value | Printed by | Setup as printed |
|---|---|---|---|
| GPT-6 AstraOpenAI, released 2026-09-03 | 40.9% | OpenAI, GPT-6 Astrachecked 2026-10-14 | - |
| GPT-5.6 SolOpenAI, released 2026-07-09 | 30.5% | OpenAI, GPT-6 Astrachecked 2026-10-14 | - |
| Claude Fable 5Anthropic, released 2026-06-09 | 34.7% | OpenAI, GPT-6 Astrachecked 2026-10-14 | - |
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.