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AI Agent Cost Simulator

Simulate multi-agent LLM costs with per-turn context growth and tool-call overhead, compare against a single agent and project monthly spend.

AI Agent Cost Simulator

Agents

Cost breakdown

AgentModelTurnsInput tokensOutput tokensCost/task
Assistantgpt-6-luna516.0K2.0K$0.0026
Total per task$0.0026

$0.0026 per task, $0.780 per month

Daily
$0.026
10 tasks
Monthly
$0.780
30 days
Yearly
$9.49
365 days

Architecture comparison

What if a single agent (using your most expensive model) handled all 5 turns sequentially?

Multi-agent (current)
$0.780
1 agents / month
Single agent alternative
$0.780
1 agent (5 turns) / month
Same cost either way

Context explosion effect

In agentic loops, each turn re-sends all prior context. A 10-turn conversation doesn't cost 10x a single turn -- it costs ~55x due to the triangular accumulation pattern.

AgentTurn 1 inputLast turn inputGrowthNaive est.ActualMultiplier
Assistant8005.6K7.0x4.0K16.0K4.0x

What this tool does

The AI Agent Cost Simulator lets you configure multi-agent architectures and see how cost grows as context accumulates across turns. Compare a multi-agent setup against a single agent, model context growth per step, and view monthly projections, so you can decide whether extra agents are worth their token cost before building the system.

Updated . Provided as is. Check the output before you rely on it in production.

How to use AI Agent Cost Simulator

  1. 1

    Add agents to your architecture

    Click Add Agent for each agent in your system. Configure the model, average turns per task, tokens per turn (input and output), and tool calls per turn.

  2. 2

    Set daily task volume

    Enter how many tasks your agent system processes per day to see daily, monthly, and yearly cost projections.

  3. 3

    Observe context growth

    Review the context growth table showing how token counts increase with each conversation turn. This is where most unexpected costs originate — context grows with every turn.

  4. 4

    Compare architectures

    Use the architecture comparison to see the cost difference between your multi-agent setup and a single-agent alternative handling the same workload.

Questions and answers

What is AI Agent Cost Simulator?
Agent cost is what an agent system spends per task, and it climbs fast because every turn re-sends the accumulated context. This simulator models each agent's model, turns, tokens per turn and tool calls, projects daily, monthly and yearly cost, and compares the setup with one agent on your priciest model.
What is context growth and why does it matter?
In multi-turn conversations, each turn adds to the context window. Turn N includes all previous turns as input, so costs grow quadratically, not linearly. A budget built from a single-turn estimate therefore understates a long agent run.
Does it send my data to a server?
No. All simulation runs in your browser using static pricing data.
Can I compare multi-agent vs single-agent architectures?
Yes. The tool includes architecture comparison mode that models the same task as multi-agent or single-agent, showing cost differences and helping you decide which approach makes economic sense.
For AI agents: how to call this tool

Machine-readable contract, endpoints and examples. Humans can ignore this section.

Best Path For Builders

Browser workflow

Runs instantly in the browser with private local processing and copy/export-ready output.

Browser Workflow

This tool is optimized for instant in-browser execution with local data handling. Run it here and copy/export the output directly.

/ai-agent-cost-simulator/

For automation planning, fetch the canonical contract at /api/tool/ai-agent-cost-simulator.json.