Why System Prompt Pricing Matters in a Cost Comparison
TokenRate's new Compare Prices grid puts every model's per-token rates, context window, and quality score in a single side-by-side view. The point: stop flipping between provider pricing pages and OpenRouter tabs. You pick a provider dropdown, check the models you want, repeat for each provider, and the grid stacks every pick into one comparison table. Most teams compare LLMs on per-token input price and call it a day. System Prompt 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. System prompts are input tokens. A 2,000-token system prompt × the model's input rate × every request = the system-prompt cost line in your monthly bill. See also: filter LLM models by tier, cost, quality, Value column vs tokens-per-dollar, and how to pick an LLM by quality score and cost.
How System Prompt Pricing Appears in the Grid
In the Compare Prices grid, the input cost column is what multiplies your system prompt. For a 2K-token system prompt and 1M requests/month at $1/M input, that's $2,000/month just in system prompt cost.
Reading the Spread
Prompt caching changes this. Most providers offer cached input at 10% of base. The Compare Prices grid shows base rates only — cached pricing modeling happens downstream in /tools/api-cost-estimator.
Practical Implications
For long system prompts, the right Compare Prices pick is whichever has the cheapest cached input (typically Anthropic Claude or Gemini). System prompts shouldn't drive the model choice — but they should drive whether caching is enabled.