Six techniques

Fewer input tokens means lower cost and more context headroom. These techniques cut token usage without sacrificing output quality. Measure each change with the token counter.

  1. 1. Trim the system prompt

    Long, repetitive system prompts are billed on every call. Keep instructions terse and move rarely-needed detail into tools or retrieval.

  2. 2. Cache the stable prefix

    If a large prefix repeats across calls, use prompt caching so it is billed at the cached rate. See the prompt caching calculator.

  3. 3. Summarize history

    Instead of resending full conversation history, summarize older turns and keep only the recent ones verbatim.

  4. 4. Retrieve less, rank better

    In RAG, fewer high-quality chunks usually beat many mediocre ones and cost far fewer input tokens.

  5. 5. Minify structured data

    Strip whitespace from JSON, shorten key names, and drop fields the model does not need.

  6. 6. Cap the output

    Set max output tokens. Output is priced higher than input, so a runaway response is expensive.

A dedicated in-browser optimizer that rewrites prompts is planned. For now, apply these techniques and verify the savings in the counter.