Cost Calculator
Compare 14 AI models for faq bot. Prices shown at 10K calls/month with default token counts.
Question answering tasks pair a user query with retrieved context for answers. Token usage depends on the context window size and the response depth. Larger context windows allow more reference material but increase the per-call cost.
The most bounded question-answering shape: a short question against a fixed knowledge base, with a short answer. Because the knowledge base never changes between calls, cache reads apply to nearly the entire input, and the effective cost per answer falls well below the list rate. A fast-tier model is usually sufficient when the answers are already written.
Recommendations
Best quality
GPT 5.4
91/100 confidence
Best value
GPT 5.6 Luna
85/100 confidence · $16/mo
Monthly estimates assume 1,500 input / 800 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 most bounded question-answering shape: a short question against a fixed knowledge base, with a short answer. Because the knowledge base never changes between calls, cache reads apply to nearly the entire input, and the effective cost per answer falls well below the list rate. A fast-tier model is usually sufficient when the answers are already written. Across the 14 models we track, a typical call uses about 1,500 input and 800 output tokens.
GPT 5.6 Luna from GPT is the lowest-cost model we track for faq bot, at roughly $16.00 for 10,000 calls per month. It scores 85 out of 100 on this task type.
GPT 5.4 from GPT ranks highest for faq bot, 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.