Cost to Run a Coding Agent for 8 Hours with LLM APIs

An AI coding agent consumes approximately 50,000 input tokens and 15,000 output tokens per hour of active use. This includes reading code context, tool calls, file diffs, and generated code. Agentic workloads are token-intensive because the model repeatedly reads and writes files. Actual usage varies significantly based on codebase size, task complexity, and how many iterations the agent needs.

Formula: cost = (input_tokens × input_price_per_Mtok + output_tokens × output_price_per_Mtok) × quantity / 1,000,000

All prices are per million tokens, sourced directly from official provider pricing pages. No fabricated numbers — every model in the table links to its detail page, which cites the official pricing source.

How much does it cost to run a coding agent for 8 hours?

It varies widely by model. Coding agents are token-intensive (~50,000 input / ~15,000 output tokens per hour), so the spread between the cheapest and most expensive models is one of the largest of any workload. The calculator above computes the exact current cost for every model, cheapest-first, from live per-million-token pricing, so you get a real hourly figure for each model instead of a stale range.

Which LLM API is cheapest for running a coding agent?

The cheapest per-hour cost comes from the models at the top of the cost table above. But coding is quality-sensitive: cheaper models may need more iterations, which raises total tokens — so the lowest sticker price is not always the lowest total cost. Compare exact hourly cost per model in the calculator, then factor in likely iterations.

How are coding agent token costs calculated?

An active coding agent uses ~50,000 input tokens/hour (code context, tool results) and ~15,000 output tokens/hour (code generation, edits). Total cost = (input_tokens × input_price + output_tokens × output_price) × hours. Prices are per million tokens from official provider pricing.