Simulator
Coding agent cost simulator
Coding agent cost simulator is built for engineering teams budgeting coding-agent runs, background tools, reasoning overhead, and context growth. Use it to decide how expensive one agent run or one developer seat becomes under realistic task patterns. Keep the workload assumptions consistent across options, then inspect the cited prices and last-checked dates before committing budget.
Open the simulator - Forecast an agent run →
The decision this page helps you make
Forecast coding-agent token spend for a developer or team, including context accumulation, prompt caching, tool calls, retries, and reasoning overhead.
The practical question is how expensive one agent run or one developer seat becomes under realistic task patterns. Use the same workload assumptions for every option so the comparison reflects billing differences instead of different inputs.
Start with these inputs
- Task shape: Files touched, turns, retries, context.
- Model behavior: Reasoning and tool-call overhead.
- Budget risk: Cost per run, developer, and team.
What the result includes
| Area | What ByteCosts shows |
|---|---|
| Task shape | Files touched, turns, retries, context |
| Model behavior | Reasoning and tool-call overhead |
| Budget risk | Cost per run, developer, and team |
How to use the result
- Run a realistic base case and a heavier-usage case before choosing a provider or plan.
- Compare alternatives with identical traffic, token, seat, runtime, and retry assumptions.
- Open the cited provider source before a purchase or production billing decision.
Formula
agentCost = basePromptCost + sum(stepInputCost + stepOutputCost + toolCallCost + retryCost), scaled by runs per developer and developers per month.
Assumptions
- Agent turns can resend context, so context growth is a real cost driver.
- Retry and tool-loop settings are planning assumptions until measured in logs.
- Model prices are list prices unless the source data says otherwise.
- The simulator estimates model spend, not developer salary or opportunity cost.
Example scenario
Estimate a coding-agent run with several turns, growing repository context, tool calls, and a retry rate. Then scale it from one developer to the whole team.
How to read the example
| Step | Example input | What to inspect |
|---|---|---|
| One run | Steps, context growth, tool calls, retries | Cost per successful task |
| One developer | Runs per day and workdays | Monthly developer cost |
| Team rollout | Developer count and power-user factor | Budget cap and alert threshold |
Interpretation guide
- High retry rate or long context usually matters more than the first prompt.
- Compare cost per successful task, not cost per token alone.
- Use caps and alerts for long-running agents before broad rollout.
Limitations
Coding agent cost simulator is a planning tool, not a billing guarantee. It uses the visible assumptions and committed source-backed data available at the page's last update.
Check the cited provider page and your own production logs before signing a contract, changing price, or committing infrastructure spend.
Frequently asked questions
What should I enter first in Coding agent cost simulator?
Start with task shape: files touched, turns, retries, context. Add optional adjustments only after the base case is understandable.
Is the result a guaranteed invoice forecast?
No. It is a planning estimate based on the visible workload assumptions and source-backed public prices. Taxes, negotiated discounts, undocumented limits, and production behavior can change the final invoice.
Where do the prices and assumptions come from?
ByteCosts keeps provider source links, confidence information, and last-checked dates attached to pricing records. User-entered workload assumptions remain separate from published vendor facts.
Coding agent cost simulator. ByteCosts. https://bytecosts.com/tools/agent-cost-simulator/