Cost Calculator
Compare 14 AI models for unit test 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.
Test generation is the rare code task where input and output are both large: you send the function under test plus its dependencies, and get back a full suite of cases. Expect 3K in, 5K out. Because the source file rarely changes between runs, cache reads pay off faster here than in almost any other use case: the same file gets resent every time you regenerate a suite.
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 3,000 input / 5,000 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.
Test generation is the rare code task where input and output are both large: you send the function under test plus its dependencies, and get back a full suite of cases. Expect 3K in, 5K out. Because the source file rarely changes between runs, cache reads pay off faster here than in almost any other use case: the same file gets resent every time you regenerate a suite. Across the 14 models we track, a typical call uses about 3,000 input and 5,000 output tokens.
GPT 5.6 Luna from GPT is the lowest-cost model we track for unit test 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 unit test 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.