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

13s

Input Tokens

563

Output Tokens

516

Cost

$0.00

Context

Input

List all vehicles that are currently in stock.

Expected output

SELECT * FROM vehicles WHERE in_stock = TRUE;

Model output

SELECT vehicle_id, make, model, year, price, in_stock
FROM vehicles
WHERE in_stock IS TRUE;