CrewAI Pricing: Free, Enterprise & Cloud Plans
CrewAI is one of the fastest-growing multi-agent frameworks in production today, with over 52,000 GitHub stars and 2 billion agent executions in the past 12 months. The core framework is free. The cloud platform starts at $0. But the real pricing story is what you spend on LLM API calls that CrewAI does not cover. Here is the complete breakdown of what you will actually pay.
Pricing Overview
CrewAI operates on a split model: the orchestration framework is open source and free, while the managed cloud platform and enterprise features carry their own pricing. Most importantly, every CrewAI deployment requires you to bring your own LLM API keys, so your largest expense will usually be the tokens your agents consume.
The table below summarizes each tier. The sections that follow break down what you actually get at each price point and where the real costs accumulate.
The Open-Source Framework
The core CrewAI framework is distributed under the MIT license and costs nothing to download, install, or run. You get the full open-source agent orchestration stack: Flows for event-driven stateful workflows, Crews for collaborative agent teams, hierarchical and sequential process modes, unified memory, and a growing library of built-in tools.
What you do not get is managed infrastructure. You are responsible for hosting, scaling, monitoring, and debugging your own deployments. For a solo developer or a small team experimenting with agentic AI systems, this is often the right starting point.
The catch: "Free" means the framework itself. Your agents need LLM inference to function, and that inference comes from providers like OpenAI, Anthropic, or Google, each with their own per-token billing. A three-agent crew running GPT-4o typically costs $0.10 to $0.20 per execution. Running the same crew on GPT-4o-mini drops that to $0.06 to $0.12.
Installing CrewAI requires Python 3.10 or later and a pip install crewai command. You will also need at least one LLM API key set as an environment variable. The CrewAI tutorial walks through the complete setup process.
Cloud Plans: Free and Professional
CrewAI AMP (Agent Management Platform) is the managed cloud offering for teams that want to deploy agents without wrangling infrastructure. It provides a visual interface for configuring crews, built-in monitoring, and automatic scaling.
Both cloud tiers still require you to bring your own LLM API keys. CrewAI AMP handles deployment, updates, and the visual interface, but the token bills from OpenAI, Anthropic, or whichever provider you connect go directly to you.
The Free plan works for testing and light workloads. At 50 executions per month, you can validate your agent architecture before committing budget. The Professional plan doubles that cap and adds a second user seat for team collaboration.
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Download Free →Enterprise Pricing
CrewAI Enterprise uses custom pricing tailored to organizational scale. There is no published rate card. You contact the sales team, describe your deployment requirements, and negotiate terms.
What you get at the Enterprise tier goes beyond execution limits. This is where governance and compliance features live:
- SOC2 compliance for regulated industries
- Single Sign-On (SSO) integration with your identity provider
- Secret manager integration for centralized credential management
- PII detection and masking on agent inputs and outputs
- Dedicated support with priority response times
- Uptime SLAs with contractual guarantees
Enterprise customers also choose between two deployment models: CrewAI AMP (fully managed SaaS at app.crewai.com) and CrewAI Factory, a containerized self-hosted option that runs on-premises or in your private cloud. Factory is the path for organizations that cannot send data to an external platform.
The Real Cost: LLM API Fees
This is where most teams underestimate their CrewAI spend. The framework is free and the cloud plan is cheap, but multi-agent systems are inherently token-hungry. Every agent in a crew makes its own LLM inference calls. Every agent-to-agent handoff passes conversation history. Every reasoning loop burns additional tokens.
The cost multipliers stack quickly. Reasoning loops (ReAct or Chain-of-Thought patterns) can consume up to 10x more tokens than a direct answer. Multi-turn agent conversations include the full conversation history with each new turn, which means token counts grow exponentially. And multi-agent coordination adds up to 4x the token usage compared to running a single agent.
Mid-sized production agents typically consume 5 to 10 million tokens per month. If you are running GPT-4o, that translates into real infrastructure spend that can easily exceed the cost of CrewAI's own platform fees.
Plan-by-Plan Cost Comparison
Here is how total cost of ownership breaks down across the three tiers for a hypothetical team running 80 workflow executions per month with a three-agent GPT-4o crew:
| Cost Component | Open Source | Free Cloud | Professional | Enterprise |
|---|---|---|---|---|
| Platform fee | $0 | $0 | $25/mo | Custom |
| Execution cap | Unlimited | 50/mo | 100/mo | Negotiated |
| LLM API (80 runs) | $8-16 | $8-16 | $8-16 | $8-16 |
| Infrastructure | Self-managed | Included | Included | Included or self-hosted |
| SSO / SOC2 / PII | DIY | No | No | Included |
| Est. monthly total | $8-16 + ops | $8-16 | $33-41 | Custom + $8-16 |
The LLM API cost is identical across all tiers because CrewAI does not mark up your provider fees. The platform fee determines what level of managed infrastructure and governance you get around those API calls.
Who Should Pay for What
Your CrewAI pricing decision depends on where you are in the build cycle:
Solo developers and experimenters: Start with the open-source framework and the Free cloud plan. You get 50 managed executions per month at no cost. Use cheaper models (GPT-4o-mini, Claude Haiku) during development to keep API bills under $10/month.
Small teams shipping to production: The $25/month Professional plan is the obvious choice. It doubles your execution cap, adds a team member, and removes the infrastructure burden. Budget $30-$80/month total including LLM costs for moderate workloads.
Enterprise deployments: If you need SOC2, SSO, PII masking, or on-premises deployment, you are in Enterprise territory. The platform fee will be the smallest part of your bill. Budget for LLM costs at scale (5-10 million tokens/month is typical for mid-sized production agents) and plan for external memory providers if you serve multiple users.
The bottom line: CrewAI's platform fees are competitive and straightforward. The variable that will make or break your budget is how you architect your agents and which LLM models you choose. Spending 80% of your design time on clear, focused task definitions rather than elaborate agent backstories is the single most effective cost optimization. For a deeper look at how CrewAI compares to alternatives like LangChain, see our CrewAI vs LangChain comparison.
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