SQL Query Builder
Natural language to SQL in milliseconds
Let non-technical users query your database using plain English. The model converts natural language questions to optimized SQL, explains the query logic, and flags potential performance issues before execution.
GPT-6 Luna
for 250K tokens a month · 75% input / 25% output
Why this model
For this workload — 250K tokens a month, 75% of them input — it comes to about $0.05 a month, the lowest of the models suggested here.
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Implementation tips
- 1
Always include your full schema (table names, column names, types, and key relationships) in the system prompt — the model cannot write correct JOINs or filter on the right columns without this context.
- 2
Add a mandatory 'EXPLAIN plan' step: ask the model to estimate query cost before generating the final SQL, and require it to add indexes to its recommendations for any query that would do a full table scan.
- 3
Implement a read-only execution sandbox: let the model generate and run SELECT queries automatically, but require human approval before any INSERT, UPDATE, or DELETE — critical for trust and safety.