1005001k5k10k50k100k
Estimated monthly total
$35.50
~$0.0355 per interaction
API (LLM)$15.00
Infrastructure$20.50
Compare providers (incl. infra)
OpenAI GPT-4o$35.50
Anthropic Claude$41.50
Google Gemini Pro$28.00
Open Source (Llama)$21.00
💡 A human agent handling this volume costs ~$3,500–5,000/month.
How to Use This Calculator
- 1. Choose your use case — This determines the typical interaction pattern and helps contextualize the cost.
- 2. Set your volume and complexity — Volume is monthly interactions. Complexity affects token usage: simple (single API call), medium (multi-step reasoning), complex (multi-agent workflow).
- 3. Compare providers — The bar chart shows cost across all providers simultaneously, so you can compare even if you have only one selected in the form.
Methodology & Assumptions
Token estimates per interaction: Simple ~700 tokens, Medium ~3,000 tokens, Complex ~8,000 tokens.
Provider pricing as of March 2026. Prices change — we update monthly.
Infrastructure costs include a base fee plus a per-thousand-interactions variable cost.
Human agent comparison assumes ~$4,000/month fully loaded cost handling ~500 interactions/month.
Frequently Asked Questions
How much does an AI agent cost?
Costs range from $50/month for simple automations using open-source models to $5,000+/month for complex multi-agent enterprise systems on GPT-4o. The biggest cost driver is LLM API usage, which depends on interaction volume and complexity.
How much does it cost to build an AI agent?
Building a basic AI agent with no-code tools like n8n costs $0–20/month. A custom-coded agent using Python frameworks like CrewAI or LangGraph costs development time plus $50–500/month in infrastructure and API costs.
What is the cheapest way to run AI agents?
Self-hosting open-source models like Llama 3 on a VPS ($50–100/month) gives the lowest per-interaction cost. For cloud-hosted options, Google Gemini Pro offers strong price-to-performance.
Are there free AI agent platforms?
Yes. n8n (self-hosted), CrewAI, LangGraph, and AutoGen are free and open-source. You still pay for LLM API usage and hosting, but the frameworks themselves cost nothing.
How do I reduce AI agent costs?
Use smaller models for routine tasks (e.g. GPT-4o-mini instead of GPT-4o), cache frequent responses, implement token budgets per interaction, and route only complex queries to expensive models.
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