How to use the data
How should you compare LLM API prices?
Start with the workload, not the model name. Estimate fresh input tokens, repeated cached context, output length, and monthly request count. LLM API Prices applies those inputs consistently so you can compare first-party and OpenRouter routes without mixing their prices or fees.
A lower list price is only useful when the model still meets your requirements. Test response quality, tool support, latency, availability, context behavior, and data policies before moving production traffic.
LLM API prices are easiest to compare when every rate uses the same unit. This site normalizes published rates to USD per one million tokens, while keeping input, cached-input, and output prices visible as separate cost components. That makes a headline rate easier to connect to the way an application actually spends tokens.
Use the calculator for a quick estimate, then compare the assumptions with your own logs. A support bot with short prompts, a coding assistant with repeated context, and a batch summarization job can produce very different monthly totals on the same model. The result is a planning reference, not a quote: confirm current provider terms, rate limits, regional rules, and billing details before production use.
Price data also needs lifecycle context. A preview, retired, self-hosted, or region-specific model should not be treated as a universal production rate. Model pages separate lifecycle notes, context windows, official sources, OpenRouter mappings, and verification dates so you can understand what a number means before comparing it.
Jev 1.13 is TypeSafe AI's structured-decision model: it returns typed choices and probabilities instead of free-form text. Its official rate is $0.042 per million input tokens with free output. Compare it with decision workloads rather than treating its zero output rate as a text-generation price advantage.
When a source is unavailable or a change looks structurally suspicious, the catalog keeps the last verified record instead of silently publishing a guess. That distinction matters for teams using the site to plan budgets: a missing update should be visible as a verification issue, not disguised as a new price.