What a million tokens costs
509 models priced across 16 sellers — 11 who resell, and 5 makers publishing their own list price (Anthropic, DeepSeek, Mistral AI, Moonshot AI, OpenAI). Where a maker sells the model itself and we have not read its rate, the row carries its price page and a ○. The lowest input rate on record is $0.0170 per million, on ibm-granite/granite-4.0-h-micro.
23 free to call →356 with cached rates →How we read these prices →
By seller
Same model, different seller
The same model varies up to 41.1× between sellers — z-ai/glm-5.2 is $0.0341 per million input tokens at OpenRouter and $1.4 at FriendliAI.
- z-ai/glm-5.241.1× · $0.0341 OpenRouter → $1.4 FriendliAI
- z-ai/glm-5.320.0× · $0.0699 OpenRouter → $1.4 FriendliAI
- moonshotai/kimi-k315.9× · $0.189 OpenRouter → $3 Fireworks AI
- deepseek/deepseek-v3.210.7× · $0.28 OpenRouter → $3 SambaNova
- openai/gpt-oss-120b7.0× · $0.05 Novita AI → $0.35 Cerebras Inference
- inclusionai/ling-3.1-flash4.0× · $0.075 OpenRouter → $0.3 Novita AI
More models than this appear in two catalogues; only these carry an input and an output rate from each seller, which is what a comparison needs.
Every model we hold both halves for
Showing 200 of 509 matching · 509 priced in total · input and output are separate prices and are never averaged
Frequently asked
What is the cheapest LLM API right now?
Why one row per model instead of one per listing?
What does “cached in” mean?
Why is the same model different prices at different sellers?
What is a batch tier?
Are free models really free?
Can a seller pay to appear higher here?
Estimate a workload
These are rates, not a bill. Put your own token mix in and the calculator prices it across every seller, cached share included.
Open the LLM cost calculator →Every rate is what that seller charges to route to the model, not the model maker’s own price · readings over 21 days old are hidden rather than shown stale · no blended cost-per-quality figure appears here, because we hold no benchmark that would support one


















