AutoGen vs n8n

Core capabilities: AutoGen vs n8n

AutoGen is a framework for orchestrating multiple LLM agents that converse to solve tasks. It provides built-in agent roles (UserProxy, Assistant, Critic), tool/function calling, and group chat patterns (RoundRobin, Selector, Swarm). The 0.4 rewrite introduced a layered architecture with a lightweight event core. n8n is a workflow automation platform with a visual builder and 400+ pre-built integrations. It includes AI agent nodes (OpenAI, Anthropic, Gemini, LangChain) that enable LLM calls, RAG, and multi-agent setups within a larger automation workflow. AutoGen excels at multi-agent conversation, while n8n excels at connecting many services and adding AI steps where needed. AutoGen wins for multi-agent conversation depth; n8n wins for breadth of integrations and ease of combining AI with traditional automations.

AI/model approach: AutoGen vs n8n

AutoGen is model-agnostic, supporting OpenAI, Anthropic, Azure, Gemini, Ollama, and local models. It does not embed a specific AI; it orchestrates LLM agents through conversations. n8n also supports multiple models via nodes (OpenAI, Anthropic, Gemini) and integrates with LangChain for more advanced chains. However, n8n's AI capabilities are built into a visual workflow—users configure LLM nodes as part of a broader automation. AutoGen's approach is more flexible for complex multi-agent interactions (e.g., planning, coding, critiquing), while n8n's AI features are designed for simpler tasks like summarization, classification, or RAG within a workflow. AutoGen wins for sophisticated multi-agent AI experiments; n8n wins for practical AI-enhanced automations.

Integrations & ecosystem: AutoGen vs n8n

AutoGen integrates with major LLM providers (OpenAI, Anthropic, Azure, Gemini, Ollama) and supports Docker and Jupyter for code execution. It is an open-source framework with a growing community but no pre-built app connectors. n8n offers 400+ pre-built integrations including Google Sheets, Gmail, Slack, Telegram, Airtable, PostgreSQL, and many more. It also provides webhook triggers, cron scheduling, and HTTP Request nodes for custom APIs. n8n's ecosystem is vastly larger for connecting to SaaS tools and databases. n8n wins decisively for integrations; AutoGen's ecosystem is limited to LLM providers and execution environments.

Performance & scale: AutoGen vs n8n

AutoGen's performance depends on the underlying LLMs and infrastructure. It is designed for batch-oriented tasks and multi-turn conversations, but may struggle with real-time or high-throughput scenarios. The framework is not optimized for production scale; it is primarily a research and prototyping tool. n8n is built for production automation, with error handling, retries, and scaling via Docker or cloud plans. n8n's execution-based pricing aligns with scale: more executions cost more. AutoGen has no cost (MIT) but requires self-hosted LLM provisioning. n8n wins for production-scale automation; AutoGen is unproven at scale beyond prototypes.

Developer experience: AutoGen vs n8n

AutoGen targets developers comfortable with Python, and the 0.4 rewrite improved developer experience with a cleaner core API. AutoGen Studio provides a visual interface for prototyping, but building production systems still requires coding. n8n prioritizes accessibility with a drag-and-drop builder, instant feedback on edits, and 9,500+ templates. Developers can also write JavaScript or Python in code nodes and use npm packages. Git version control is available for self-hosted instances. n8n wins for developer experience and speed of building automations; AutoGen is better for deep customization of agent behavior.

AutoGen pricing (2026)

AutoGen is completely free and open source under the MIT license. There are no paid tiers or hidden costs. You pay only for the LLM API usage (e.g., OpenAI, Anthropic) and infrastructure (e.g., cloud compute for self-hosting AutoGen). AutoGen Studio—the visual UI for prototyping—is included at no extra cost. As of 2026, there is no official commercial support or enterprise offering from Microsoft for AutoGen, though the community provides assistance through GitHub.

n8n pricing (2026)

n8n operates on a freemium model with three plans as of 2026:

• Community: $0. Self-hosted, unlimited workflows, full features, Git version control. No cloud hosting or sharing.
• Starter: $20/month. Cloud-hosted, 5 workflows, limited executions (exact number not published; n8n states "fair use"). No sharing or advanced features.
• Pro: $50/month. Cloud-hosted, unlimited workflows, workflow sharing, multiple environments (dev/prod). Execution limits apply based on plan (details on n8n pricing page).

Additional costs: LLM API keys if you use AI agent nodes (OpenAI, Anthropic, etc.) are billed separately by those providers. Self-hosting incurs infrastructure costs (server, Docker, storage). Paid plans include SLA guarantees only on higher tiers (typically business plans not listed here).

Value-per-dollar: AutoGen vs n8n

AutoGen offers the best value for researchers and developers who are comfortable coding and want to experiment with multi-agent AI without upfront costs. The total cost is LLM API usage plus infrastructure. For teams building production automations that involve many integrations and minimal code, n8n's Community plan (self-hosted) is free and powerful, but requires operational overhead. The Starter and Pro plans are affordable compared to Zapier ($30/mo for 750 tasks) and Make ($9/mo for 10k operations). However, n8n's execution-based pricing can scale unpredictably for high-volume use. AutoGen wins for cost if your primary need is multi-agent AI; n8n wins for cost per integration in business automation where the number of integrations and workflows justifies the plan.