Cost Calculator
Compare 14 AI models for categorization. Prices shown at 10K calls/month with default token counts.
Classification tasks assign labels or categories to input text with minimal output. These are the most token-efficient task type across all major AI providers. Input stays short, and output is typically a single label or confidence score.
Classification into a fixed taxonomy is token-efficient by construction: the taxonomy is the same on every call and the output is one label. Put the taxonomy in the cached prefix and the marginal cost per item approaches the cost of the item text alone. Model tier matters less here than in any other use case tracked.
Recommendations
Best quality
GPT 5.4
88/100 confidence
Best value
GPT 5.6 Luna
91/100 confidence · $16/mo
Monthly estimates assume 800 input / 150 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.
Classification into a fixed taxonomy is token-efficient by construction: the taxonomy is the same on every call and the output is one label. Put the taxonomy in the cached prefix and the marginal cost per item approaches the cost of the item text alone. Model tier matters less here than in any other use case tracked. Across the 14 models we track, a typical call uses about 800 input and 150 output tokens.
GPT 5.6 Luna from GPT is the lowest-cost model we track for categorization, at roughly $16.00 for 10,000 calls per month. It scores 91 out of 100 on this task type.
GPT 5.4 from GPT ranks highest for categorization, scoring 88 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.