LLM price comparison
Every major model's API pricing in one live table — sort by input or output cost, filter by provider, and see what a request of your size costs on each. Prices load fresh from OpenRouter every time, so the table never goes stale.
How to read LLM pricing
Providers bill per token with separate input and output rates, quoted per million tokens. Output tokens usually cost 3-5× input tokens, so response length drives spend more than prompt size for chatty workloads — while RAG workloads with big retrieved contexts are dominated by the input rate. The per-request column multiplies both rates by the token counts you set above, which is the number that actually matters when comparing models for a workload.
A cheap model that needs two attempts isn't cheap, and a premium model on a short prompt often costs less than intuition suggests — a 2,000-token question to a frontier model is still a fraction of a cent. Compare with your own token counts, then sanity-check monthly totals in the LLM cost calculator.
More free tools
- LLM cost calculator — Estimate per-request, daily, and monthly spend from token counts and request volume.
- RAG cost calculator — Full pipeline costs — embeddings, vector storage, and generation — from corpus size and query volume.
- RAG chunking visualizer — Paste a document and watch chunk size, overlap, and strategy change the chunks before you embed.
- LLM context window comparison — Count the tokens in any text and check which models it fits, against live context windows.
- Tool call & MCP schema builder — Build function-calling parameters once, copy valid JSON Schema for OpenAI, Anthropic, and MCP.
- AI chatbot ROI calculator — Turn ticket volume, handle time, and deflection rate into monthly support savings and ROI.