Six Ways to Cut Your LLM API Bill in Half

Last verified August 2026.

1. Prompt caching

If your requests repeat the same system prompt, tool definitions, or reference documents, prompt caching charges a fraction of the normal input rate for the repeated portion — commonly 90% off on cached reads. For agents that resend the same growing context on every step (see why agent costs run high), this is usually the single biggest lever available.

2. Batch processing

For anything that doesn't need a response in real time — bulk classification, offline summarization, data labeling — batch APIs typically cut both input and output cost by 50%. If your workload can tolerate a delay of a few minutes to hours, this is close to free money.

3. Model routing by task difficulty

Not every step in a workflow needs the flagship model. A common pattern: use a cheap, fast model (DeepSeek V4 Flash, Grok 4.1 Fast, GPT-5.6 Luna) for classification, extraction, and simple formatting steps, and reserve the expensive flagship model only for the step that actually requires strong reasoning. This alone can cut blended cost dramatically since most agent steps are mechanical, not hard.

4. Trim context instead of resending everything

Rather than replaying full conversation history and every tool output on each step, summarize or drop context that's no longer relevant to the current decision. This directly reduces the "overhead multiplier" that makes agent costs balloon — see the Agent Cost Estimator to see how much a lower multiplier saves.

5. Cap output length explicitly

Since output tokens cost several times more than input tokens, an unbounded max-token setting is one of the easiest silent cost leaks. Setting a sensible max-output limit per step, and instructing the model to be concise, has a direct and immediate effect on the bill.

6. Shop the tier, not just the provider

Nearly every provider now offers a budget, mid, and flagship tier at very different price points from the same company. Before switching providers entirely, check whether a cheaper tier from your current provider already meets the bar for a given step — it's usually the least disruptive way to cut cost, since the API and behavior stay similar.

Run your own numbers against these levers using the cost comparison or agent estimator.