Five ways to cut your LLM API bill without losing quality
Prompt caching, model routing, output limits, batching small calls and measuring real usage — practical levers that lower cost per request.
2026/10/05 · API ManyToken prices keep falling, yet LLM bills keep growing because usage grows faster. The cheapest token is the one you never send. These five levers usually matter more than haggling over the per-million price.
1. Cache the stable part of your prompt
System prompts, tool definitions and long reference documents rarely change between requests. Models with prompt caching bill repeated prefixes at a fraction of the input price. Put stable content first and the user-specific part last so the cache can match.
2. Route by difficulty
Not every request needs a frontier model. A small, fast model can classify the request and handle the easy majority, escalating only hard cases. With one API key for every model, routing is just choosing a different model string.
3. Limit output
Output tokens cost several times more than input tokens. Set max_tokens, ask for structured JSON instead of prose, and tell the model the length you need.
4. Stop paying for failures
Retries after timeouts and errors quietly double costs on some providers. On API Many, failed and rejected requests are not charged, and an Idempotency-Key makes retries safe.
5. Measure per feature
Create one API key per feature or environment. The usage page breaks spend down by key and by model, so you can see which feature is expensive before the invoice does.
この記事のモデルはすべて API Many で使えます。$10 から従量課金。