Cost Calculator
Compare 14 AI models for email summarization. Prices shown at 10K calls/month with default token counts.
Summarization tasks compress long documents into concise overviews for faster reading. These tasks are input-heavy because the full source text must be included. Output stays relatively short compared to the original source document length.
Individually cheap, collectively expensive. A single thread is small, but summarization runs across an inbox at volume, so per-call price multiplied by message count is the number that matters, not the cost of any one summary. This is the use case where a fast-tier model and batch processing usually beat a smarter model outright.
Recommendations
Best quality
Claude Sonnet 5
91/100 confidence
Best value
GPT 5.6 Luna
84/100 confidence · $16/mo
Monthly estimates assume 3,000 input / 500 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.
Individually cheap, collectively expensive. A single thread is small, but summarization runs across an inbox at volume, so per-call price multiplied by message count is the number that matters, not the cost of any one summary. This is the use case where a fast-tier model and batch processing usually beat a smarter model outright. Across the 14 models we track, a typical call uses about 3,000 input and 500 output tokens.
GPT 5.6 Luna from GPT is the lowest-cost model we track for email summarization, at roughly $16.00 for 10,000 calls per month. It scores 84 out of 100 on this task type.
Claude Sonnet 5 from Claude ranks highest for email summarization, scoring 91 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.