# Understanding LLM API pricing
Large Language Model APIs charge based on token usage, not time or requests. Every API call has two costs: the input cost (processing your prompt) and the output cost (generating the response). Understanding this split is key to estimating your monthly bill accurately.# Input tokens vs output tokens
Input tokens
Input tokens represent everything sent to the model: your system prompt, conversation history, and user message. They are cheaper because the model processes them in parallel. A typical system prompt of 200 words costs roughly 267 input tokens.
Output tokens
Output tokens are generated one by one in sequence, making them more computationally expensive. Most providers charge 3-5× more for output tokens. A 300-word response generates roughly 400 output tokens. Keeping responses concise is one of the most effective cost-saving strategies.
# Choosing the right model for your budget
Start with a capable mid-tier model like
Not all tasks require the same model quality. Classification, extraction, and summarization tasks often perform well with smaller, cheaper models. Reserve large frontier models like GPT-4o mini or Gemini 1.5 Flash and only upgrade if quality falls short. The cost difference between a small and large model can be 10-100×. claude-3-opus or o1 for complex reasoning tasks where quality directly affects outcomes.