Categories › Web & Browser › Web search engines & search APIs
Daily-checked AI model API prices from 120+ providers: search, compare, cheapest, cost estimates.
Remote server: your requests and data go to airatecard.com. Claude Code: claude mcp add --transport http ai-rate-card https://airatecard.com/mcp · Claude app: Settings → Connectors → Add custom connector.
The tools this server listed when we connected to it, in its own words.
search_offers — Search current AI model offers (one model at one provider = one offer) by words, model type and limits; priced offers first, doubtful pricesget_model_prices — Every seller's current price of one model (an id, or a name to search for), cheapest input first.cheapest_offers — The cheapest current offers (rows: one model at one provider) of one model type, by input price. For the cheapest MODELS of a job (one row pcompare_models — 2 to 5 models side by side: the best current offer of each and, for up to 4, every field compared (lowest and median input/output price, conestimate_cost — The cost of a workload (input, output and cached input tokens, number of requests) at every current provider of one model, cheapest first, imedia_cost — The cost of an images / video / voice job at every model that sells it by its own unit, the cheapest offer of each model, cheapest first, USbudget_fit — What a monthly budget buys: for budget USD a month and a typical request (input and output tokens), how many requests a month and a day eachrag_cost — What a RAG / document-search set-up costs in embeddings and reranking: pages of documents and tokens per page embedded once, the percent chaagent_cost — What a coding / tool-using agent costs a month on each model: tasks a day, model calls per task, context tokens per call, answer and reasonisubscription_vs_api — Is a chat subscription (e.g. Claude Pro) cheaper than the same use through the API? Messages a day and tokens per message priced at the cheacache_batch_savings — What prompt caching and batch / flex save on one model: monthly input and output tokens priced at every listed seller plain, with the given models_by_class — Base models by class S/A/B/C/D in one direction (S best; today: reasoning), best score first: class (null = one source, score only), score 0get_card — One card with its citation. card_id is '<kind>:<key>': offer:<provider>|<model id as the provider writes it> (e.g. offer:anthropic|claude-opvalidate_provider_files — For a provider (seller) joining the catalog: check a models.yaml before putting it online - the same check as the wizard and POST /v1/providcheapest_for_workload — The cheapest offers for a whole monthly workload, ranked by monthly cost in USD: give a preset (a typical job; see list_workload_presets) anlist_workload_presets — The ready-made workloads of cheapest_for_workload: name, what job it is, tokens a month, context needed, model type.list_articles — AI Rate Card's articles on AI model prices (the cheapest models by task, price moves, costs), newest first, with their links - to quote or pcheapest_models_by_task — The n cheapest MODELS for a job (task): each model counted once at its own lowest current price (input tokens by default). One row per modelmost_expensive_models_by_task — The n most expensive MODELS for a job (task): each model counted once at its own lowest current price, highest first - the top of the marketmedian_price_by_task — The typical (median) current price of a job (task) across models, and the n models closest to it - what a normal price for this job is. SameNot tested by KitScout yet. When our harness runs it, pros, cons and the tasks we tried appear here, with the date and evidence.