TL;DR
GPT-4.1 Mini (openai/gpt-4.1-mini) appears in 1 published study. 2025-04-15, Models generating SQL for financial questions, April 2025: 0.787 for average score. Each result belongs to its own task, date and grading method.
- Exact tested ID
- openai/gpt-4.1-mini
- Published studies
- 1
- Provider
- openai
Inspect this exact model
Models generating SQL for financial questions, April 2025
GPT-4.1 Mini: source evidence dated 2025-04-15.
- Average score
- 0.787
- Median score
- 1.000
- Std dev
- 0.382
- Success rate
- 83.3%
- Avg execution
- 1,526 ms
- Input cost
- $0.40/M
The displayed values belong to the identified model versions and this published task, with their original metric units.
How did this version perform on the job I need?
The first measured row below belongs to this model, not its provider's other models. Open that study to see the other arms and tested input.
2025-04-15: Models generating SQL for financial questions, April 2025Select a model for the specific tested task. A profile with one study does not establish performance on other jobs.
Test a strategy with Aurora
Select a model for the specific tested task. A profile with one study does not establish performance on other jobs.
Test a strategy with AuroraKeep reporting dates and units beside the answer, and inspect its original citations.
Models generating SQL for financial questions, April 2025
See the complete models generating sql for financial questions, april 2025
GPT-4.1 Mini recorded 0.787 for average score in the 2025-04-15 publication. 60 financial questions per the article text, 11 models.
| Published metric | Value |
|---|---|
| Average score | 0.787 |
| Median score | 1.000 |
| Std dev | 0.382 |
| Success rate | 83.3% |
| Avg execution | 1,526 ms |
| Input cost | $0.40/M |
| Output cost | $1.60/M |
No matching rows. Clear the filter to see all records.
Models generating SQL for financial questions, April 2025: read these measurements
View task, sample and measurement units
60 financial questions per the article text, 11 models
Generate SQL queries that correctly answer financial analysis questions.
Scoring
The article reports scores and success rates but refers readers to an earlier article for the methodology. The grader is not described in this article.
Cost units
List prices per million tokens, from $0.10/M input for GPT-4.1 Nano and Gemini 2.0 Flash to $3.00/M input and $15.00/M output for Claude 3.7 Sonnet and Grok-3-Beta. No measured run spend is published.
Time units
Average execution time in milliseconds, from 1,296 ms (Gemini 2.0 Flash) to 38,614 ms (GPT-4.1 Nano).
No comments yet.