Evidence for this exact version
The results apply to the exact model ID above. Newer versions need their own evaluation. Scores with different grading scales are kept separate, and a model result alone does not evaluate a complete trading agent.
The provider name identifies the model family. The tools and harness around the model determine what it can do.
Use these results to choose a test
Start with the study closest to your task. Compare this version with the other models in that study using the same rubric and cost units. A strong result on planning does not establish stock-screening or coding quality.
Before adopting a version, try representative inputs in your own harness. Check failure cases and valid outputs alongside score, elapsed time and billed cost. The tables below describe the published runs; they are not current price quotes or live-return forecasts.
Models answering 22 stock questions with SQL
GPT 5 Mini recorded 0.664 for average score in the 2026-08-08 publication. 22 natural-language questions; 6 published model rows.
Study-wide context: Gemini 3.6 Flash has the highest published average answer score (0.841) and success rate (86.4%) in this six-row SQL comparison. GPT 5.6 Luna scores 0.550 on the same table.
These are the August study’s exact versions, data and questions. They do not establish the best model for every stock-research task or current production defaults.
A successful SQL query is not a profitable investment strategy. No return or trading signal performance is measured in this table.
Answer scores depend on the question corpus and grading process. Changing schemas, tools or prompts can change the ranking.
| Average score | 0.664 |
| Median | 1.00 |
| Success rate | 68.2% |
| Avg execution | 41.5s |
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