Opper

SQL

Natural language to SQL query generation evaluates text-to-query fidelity and schema reasoning. This task is particularly relevant for analytics chat assistants and simplified database interfaces where users need to query data using natural language. Models must understand both the intent behind the question and the structure of the underlying database schema.

SQL – openai/gpt-5-nano Task | Opper AI

Input Tokens

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Output Tokens

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Duration

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Cost

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Context

Input

Find the name of the dealership that has the highest total revenue from vehicle sales

Expected output

SELECT d.name FROM dealerships d JOIN sales s ON d.branch_id = s.branch_id GROUP BY d.name ORDER BY SUM(s.sale_price) DESC LIMIT 1;

Model output

WITH revenue AS ( SELECT d.branch_id, d.name, SUM(s.sale_price) AS total_revenue FROM dealerships d JOIN sales s ON s.branch_id = d.branch_id GROUP BY d.branch_id, d.name ) SELECT name FROM revenue WHERE total_revenue = (SELECT MAX(total_revenue) FROM revenue);