Why Tool-Use Pricing Matters in a Cost Comparison
Once you've narrowed a model shortlist on the main TokenRate calculator, the Compare Prices side-by-side view is where you stack them for a decision. Each row shows the provider, the model ID (the one you'd paste into your SDK), per-1M input and output costs, the context window, and the blended quality score. Most teams compare LLMs on per-token input price and call it a day. Tool-Use Pricing is one of the under-attended dimensions that shows up in the Compare Prices grid — and ignoring it is where the surprise bills come from. Tool-use itself doesn't add a surcharge on any major provider. But the cost-per-tool-call is the input tokens (schema + history) × the model's input rate. For the underlying math, see tokens-to-dollars conversion; for routing strategy see multi-model routing with quality scores.
How Tool-Use Pricing Appears in the Grid
In the Compare Prices grid, watch the input cost column for tool-use workloads. Tool schemas are typically 200-2,000 input tokens per call; if you do 10 calls in a loop, that compounds.
Reading the Spread
Output cost for tool-use is usually small per call (compact tool args). Output ratio matters less than for content generation.
Practical Implications
For tool-use loops, the right Compare Prices pick is often a balanced-tier model with strong tool-use quality (Sonnet 4.7, GPT-5). Flagship models add cost without proportional accuracy gain.