Cost Calculator
Compare 14 AI models for sql generation. Prices shown at 10K calls/month with default token counts.
Code generation tasks send a natural language prompt and receive executable code back. Token usage tends to be input-heavy with system instructions and added context. Output scales with the complexity of the code the model generates.
The cheapest code use case on this list. A natural-language question plus a schema fits in 1.5K tokens, and the query that comes back is under 1K. That makes SQL generation a genuine candidate for a fast-tier model: the task is well-bounded, the output is short, and the quality gap between tiers narrows when there is little room to go wrong. Schema caching cuts the input side to near zero.
Recommendations
Best quality
Claude Opus 4.8
95/100 confidence
Best value
Claude Sonnet 5
93/100 confidence · $140/mo
Budget pick
GPT 5.6 Luna
70/100 confidence · $16/mo
Monthly estimates assume 1,500 input / 1,000 output tokens per call. Use the detailed page for custom calculations.
Confidence scores are a third-party benchmark snapshot from week 29 of 2026. This snapshot is 8 weeks old, so treat the scores as directional and validate against your own evals.
The cheapest code use case on this list. A natural-language question plus a schema fits in 1.5K tokens, and the query that comes back is under 1K. That makes SQL generation a genuine candidate for a fast-tier model: the task is well-bounded, the output is short, and the quality gap between tiers narrows when there is little room to go wrong. Schema caching cuts the input side to near zero. Across the 14 models we track, a typical call uses about 1,500 input and 1,000 output tokens.
GPT 5.6 Luna from GPT is the lowest-cost model we track for sql generation, at roughly $16.00 for 10,000 calls per month. It scores 70 out of 100 on this task type.
Claude Opus 4.8 from Claude ranks highest for sql generation, scoring 95 out of 100. Confidence scores are a third-party benchmark snapshot from week 29 of 2026. This snapshot is 8 weeks old, so treat the scores as directional and validate against your own evals.
These are estimates based on published rates. Track your real spend with the free dashboard.