Enter your token volume once and see every model ranked from cheapest to priciest — GPT-4o, GPT-4.1, o1, Claude, Gemini, DeepSeek, and Mistral, side by side.
Enter your details and click Calculate to see results
With more than a dozen viable LLM APIs on the market in 2026 — from OpenAI's GPT-4o and o1 family to Anthropic's Claude Sonnet and Opus line, Google's Gemini models, and fast-moving open-weight options like DeepSeek V3/R1 and Mistral Large — picking a model by price alone has become genuinely hard to do in your head. This LLM API cost calculator takes one input/output token profile and one request volume and instantly ranks all 14 models from cheapest to priciest, so you can see exactly where your chosen model sits relative to every alternative at your specific usage pattern.
You enter the input tokens and output tokens for a typical request, plus how many requests you expect per day. The calculator applies each model's published per-million-token input and output price to compute a cost per request, then multiplies by your daily volume and by 30 to project a monthly cost for every model at once. Models are sorted from cheapest to most expensive monthly cost, and your chosen "primary" model is highlighted in the ranking, alongside the overall cheapest option, so you can see the price gap directly.
The relationship between input price and output price is not the same across providers — a model that looks cheap on input tokens can be one of the pricier options once your output length grows, because output tokens are billed at 3-5x the input rate almost everywhere. Ranking every model side by side at your actual token mix avoids the common mistake of comparing headline "per 1M tokens" prices without accounting for how input-heavy or output-heavy your workload really is.
The cheapest model at your token volume may still lack the reasoning depth, context window, or reliability your task needs. Use the ranking to shortlist a few affordable candidates, then validate quality before committing production traffic.
Because output tokens are priced several times higher than input tokens on nearly every provider, trimming response length (structured output, lower max_tokens, stop sequences) often saves more than switching models entirely.
LLM pricing has shifted meaningfully multiple times a year across every major provider as new model generations ship. Bookmark this calculator and re-run it before renewing any budget or contract.
Common questions about comparing LLM API pricing
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