--- title: "camel vs crewAI" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/camel-ai-camel-vs-crewaiinc-crewai" tools: ["camel-ai-camel", "crewaiinc-crewai"] --- # camel vs crewAI Neutral, constraint-first comparison with live GitHub stats. | | [camel](/tools/camel-ai-camel.md) | [crewAI](/tools/crewaiinc-crewai.md) | | --- | --- | --- | | Tagline | CAMEL: The first and the best multi-agent framework | Fast and Flexible Multi-Agent Automation Framework | | Stars | 17,346 | 55,132 | | Forks | 1,989 | 7,752 | | Open issues | 450 | 617 | | Language | Python | Python | | Adopt for | camel | CrewAI is an open-source Python framework used to orchestrate autonomous AI agents, enabling them to collaborate effectively on complex tasks. Users can leverage high-level abstractions and low-level APIs for development | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | AI Agents, Model Training | AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [camel](/tools/camel-ai-camel.md) | [crewAI](/tools/crewaiinc-crewai.md) | | --- | --- | --- | | Days since push | 1d | 0d | | Open issues (now) | 450 | 617 | | Full report | [trust report](/tools/camel-ai-camel/trust.md) | [trust report](/tools/crewaiinc-crewai/trust.md) | **Typed relationship:** camel _(alternative)_ crewAI Both CAMEL and crewAI are multi-agent automation frameworks aimed at enabling real business value through various use cases such as infrastructure automation, productivity workflows, and collaborative research. They address similar problems with different approaches. ## Shared compatibility - **Python**: [camel](/tools/camel-ai-camel.md) - Python runtime; [crewAI](/tools/crewaiinc-crewai.md) - Python runtime ## Decision facts: camel - **Pricing:** freemium - Free and open-source with an Apache-2.0 license allowing for commercial use, modification, distribution. - **Requirements:** Min 8 GB RAM; Requires Docker - **Adopt for:** camel - **License detail:** Apache-2.0 ## Decision facts: crewAI - **Adopt for:** CrewAI is an open-source Python framework used to orchestrate autonomous AI agents, enabling them to collaborate effectively on complex tasks. Users can leverage high-level abstractions and low-level APIs for development ## Choose when ### Choose camel if… - License: camel is Apache-2.0, crewAI is MIT. - Pricing: Free and open-source with an Apache-2.0 license allowing for commercial use, modification, distribution.. - Requirements: Min 8 GB RAM; Requires Docker. - Both CAMEL and crewAI are multi-agent automation frameworks aimed at enabling real business value through various use cases such as infrastructure automation, productivity workflows, and collaborative research. They address similar problems with different approaches. - Tags unique to camel: communicative-ai, deep-learning, artificial-intelligence, ai-societies. - Also covers Model Training. - - When you need a comprehensive framework for developing and studying multi-agent systems that includes various types of agents, tasks, prompts, models, and simulated environments. ### Choose crewAI if… - License: crewAI is MIT, camel is Apache-2.0. - Both CAMEL and crewAI are multi-agent automation frameworks aimed at enabling real business value through various use cases such as infrastructure automation, productivity workflows, and collaborative research. They address similar problems with different approaches. - Tags unique to crewAI: llms, agents, aiagentframework, ai-agents. - - Use CrewAI when you need a flexible, production-ready solution to develop multi-agent workflows that emphasize collaborative intelligence and autonomy. ## When NOT to use camel - - When you're working on projects that require a more specialized tool for single-agent systems or tasks not related to multi-agent interaction. - - If your research does not need the breadth of functionalities provided by camel, such as if it focuses solely on specific aspects like only model training without requiring extensive simulated agent ## When NOT to use crewAI - - Avoid using CrewAI if you require immediate support for a proprietary language or framework not natively supported by the Python ecosystem. - - Do not use CrewAI when your project strictly demands a closed-source solution and lacks tolerance for open-source licensing. ## Common questions ### What is the difference between camel and crewAI? camel: CAMEL: The first and the best multi-agent framework. crewAI: Fast and Flexible Multi-Agent Automation Framework. See the comparison table for live GitHub stats and shared categories. ### When should I choose camel over crewAI? Choose camel over crewAI when License: camel is Apache-2.0, crewAI is MIT; Pricing: Free and open-source with an Apache-2.0 license allowing for commercial use, modification, distribution.; Requirements: Min 8 GB RAM; Requires Docker; Both CAMEL and crewAI are multi-agent automation frameworks aimed at enabling real business value through various use cases such as infrastructure automation, productivity workflows, and collaborative research. They address similar problems with different approaches; Tags unique to camel: communicative-ai, deep-learning, artificial-intelligence, ai-societies; Also covers Model Training; - When you need a comprehensive framework for developing and studying multi-agent systems that includes various types of agents, tasks, prompts, models, and simulated environments. ### When should I choose crewAI over camel? Choose crewAI over camel when License: crewAI is MIT, camel is Apache-2.0; Both CAMEL and crewAI are multi-agent automation frameworks aimed at enabling real business value through various use cases such as infrastructure automation, productivity workflows, and collaborative research. They address similar problems with different approaches; Tags unique to crewAI: llms, agents, aiagentframework, ai-agents; - Use CrewAI when you need a flexible, production-ready solution to develop multi-agent workflows that emphasize collaborative intelligence and autonomy. ### When should I avoid camel? - When you're working on projects that require a more specialized tool for single-agent systems or tasks not related to multi-agent interaction. - If your research does not need the breadth of functionalities provided by camel, such as if it focuses solely on specific aspects like only model training without requiring extensive simulated agent ### When should I avoid crewAI? - Avoid using CrewAI if you require immediate support for a proprietary language or framework not natively supported by the Python ecosystem. - Do not use CrewAI when your project strictly demands a closed-source solution and lacks tolerance for open-source licensing. ### Is camel or crewAI more popular on GitHub? crewAI has more GitHub stars (55,132 vs 17,346). Stars measure visibility, not whether either tool fits your constraints. ### Are camel and crewAI open source? Yes - both are open-source projects on GitHub (camel: Apache-2.0, crewAI: MIT). ### Where can I find alternatives to camel or crewAI? GraphCanon lists graph-backed alternatives at /tools/camel-ai-camel/alternatives and /tools/crewaiinc-crewai/alternatives (/tools/camel-ai-camel/alternatives.md, /tools/crewaiinc-crewai/alternatives.md), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at /compare/camel-ai-camel-vs-crewaiinc-crewai.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, camel or crewAI? camel: Very active. crewAI: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for camel and crewAI? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: camel: /tools/camel-ai-camel/trust; crewAI: /tools/crewaiinc-crewai/trust. --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=camel-ai-camel`](/api/graphcanon/graph?tool=camel-ai-camel) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_