How much you save switching from one model to another.
A cheaper model that fails half the tasks isn't cheaper β it's rework. Prove quality on a sample, then bank the savings. Route by difficulty using the AI agent cost calculator.
The AI Cost Savings Calculator estimates what you spend on large language model API usage and compares two models side by side. It multiplies your calls per month by the input tokens and output tokens per call to find your total monthly token volume, then applies each model's separate input and output per-million-token rates. Because output tokens are usually priced higher than input tokens, the split matters: a chatty model that returns long responses can cost far more than the per-call figure suggests. The tool reports Model A versus Model B and shows the monthly and yearly savings from switching, so the main drivers are your call volume, average response length, and the gap between the two price schedules.
The key trade-off to watch is that the cheaper model per token is not automatically cheaper in practice. A lower-priced model may need more output tokens, extra retries, or longer prompts to reach the same quality, which erodes the headline savings this calculator shows. Use realistic average token counts rather than best-case numbers, since a handful of long calls can dominate the bill, and revisit the estimate whenever your prompts, traffic, or the providers' published rates change.
Compute each model's cost on the same usage (calls Γ tokens Γ price) and subtract. The difference is your saving. Always validate that the cheaper model still meets your quality bar.
No. Savings only count if the model still does the task well. Route simple work to the cheap model and keep a premium model for hard cases β often the best of both.