Cost Calculator
Compare 14 AI models for customer support 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.
Support bots combine RAG's retrieved context with a chatbot's growing history, so they carry both cost curves at once. Volume is high and margins per conversation are thin, which makes the per-call rate matter more than in almost any other use case here. Caching the knowledge base and product context is the single highest-leverage change.
Recommendations
Best quality
GPT 5.4
91/100 confidence
Best value
GPT 5.6 Luna
85/100 confidence · $16/mo
Monthly estimates assume 3,000 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.
Support bots combine RAG's retrieved context with a chatbot's growing history, so they carry both cost curves at once. Volume is high and margins per conversation are thin, which makes the per-call rate matter more than in almost any other use case here. Caching the knowledge base and product context is the single highest-leverage change. Across the 14 models we track, a typical call uses about 3,000 input and 1,000 output tokens.
GPT 5.6 Luna from GPT is the lowest-cost model we track for customer support 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 customer support 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.