Which LLM API is cheapest?
There is no single answer: the cheapest model depends on your mix of fresh input, cached input and output tokens, and on the cheapest model that still passes your quality bar. Prices also change often, so compare current prices on your own workload rather than trusting a ranking.
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Why rankings mislead
Providers price input, cached input and output separately, and the ratios differ. A model with cheap output can lose to one with cheap cached input on a workload that resends long prompts. The same total token count can cost very different amounts depending on the split.
The real unit is cost per finished task. A cheaper model that needs longer prompts, more retries or more human fixes can cost more overall.
How to compare
- 1Log a sample of real requests with their input, cached and output tokens.
- 2Build a small set of evals from real cases with a pass mark.
- 3Run the candidate models on the evals and keep the ones that pass.
- 4Price the passing models on your token mix using current prices, including batch and caching discounts you can actually use.
- 5Consider model routing: a small model for easy requests and a larger one only for hard ones.
Check it for your case.
Common follow-up questions.
Is an open model always cheaper?
Not always. Hosted open models can be cheap per token, and self-hosting swaps token fees for machines and engineering time. Compare total cost.
Do cheaper models hurt quality?
Sometimes, on some tasks. That is why evals come first: they show where a smaller model is good enough.
Where can I see current prices?
Our LLM API pricing page lists provider prices with a source and a checked date. Always confirm on the provider's own page before committing.
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