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.

Duration

24s

Input Tokens

839

Output Tokens

2040

Cost

$0.00

Context

Input

Show the names of customers who paid more than the average sale price for the vehicles they bought.

Expected output

SELECT c.name FROM customers c JOIN sales s ON c.customer_id = s.customer_id WHERE s.sale_price > (SELECT AVG(s2.sale_price) FROM sales s2 WHERE s2.vehicle_id = s.vehicle_id);

Model output

WITH avg_model_sales AS (
    SELECT
        v.model,
        AVG(s.sale_price) AS average_sale_price_for_model
    FROM
        sales s
    JOIN
        vehicles v ON s.vehicle_id = v.vehicle_id
    GROUP BY
        v.model
)
SELECT DISTINCT
    c.name
FROM
    customers c
JOIN
    sales s ON c.customer_id = s.customer_id
JOIN
    vehicles v ON s.vehicle_id = v.vehicle_id
JOIN
    avg_model_sales ams ON v.model = ams.model
WHERE
    s.sale_price > ams.average_sale_price_for_model;