AI Content Hub

Your system prompt is sent with every API request and billed as input tokens every time. A 2,000-token system prompt on 100,000 daily calls equals 200M tokens/day just in system prompts. Keep system prompts concise, or use prompt caching to amortize the cost.

Always set max_tokens in your API calls to prevent runaway generation. A missing token limit on a recursive agent loop can generate tens of thousands of tokens in seconds, leading to unexpected bills.

The cost of LLM API calls has fallen dramatically since 2023. GPT-3.5-Turbo launched at $2/M input tokens; by 2026, comparable-quality models like Gemini Flash and GPT-4o-mini cost under $0.15/M input tokens — a reduction of over 90% in under three years.

Many LLM APIs allow you to specify which fields you want in the response. Only request the data you need (e.g., just the generated text, not full logprobs if unused) to reduce data transfer and processing.

Implement caching strategies for repeated queries to reduce API calls and costs.

If you have many small, independent tasks for an LLM, batch them into a single API call if the model and API support it, rather than many separate calls. This can reduce overhead.