n8n vs AutoGPT: 2026 comparison

n8n and AutoGPT in brief

n8n and AutoGPT both support visual automation involving AI agents. n8n emphasizes connecting applications, code and agents, while AutoGPT focuses on specialized agents and automated routines. Both are described as open source projects and can be self-hosted. Their main differences include available interfaces, listed model support and community activity indicators. Pricing information is uneven: the supplied record describes an n8n plan but gives no AutoGPT price. That limits how confidently you can compare their overall deployment costs.

n8n : n8n builds visual workflows connecting applications, custom code and AI agents, with cloud and self-hosted deployment options.

AutoGPT : AutoGPT creates agents and visual workflows for recurring tasks, with self-hosting. [Source](https://github.com/Significant-Gravitas/AutoGPT).

Both meet the same need, which makes the comparison useful. We compare them on 11 verifiable criteria, using the same data as their profiles, collected from official sites and GitHub.

Comparison table

Criterion by criterion

For each criterion: why it matters, each one's value and who has the edge. A criterion without data on both sides is not decided.

Popularity (GitHub stars)

Stars measure developer interest; a widely followed project has more tutorials, integrations and answers. n8n : 208.5K. AutoGPT : 187.7K. Edge: n8n.

Activity over a year

Commits over 52 weeks show whether the project moves fast, fixes bugs and keeps up with new models. n8n : 14,403 commits. AutoGPT : 4,401 commits. Edge: n8n.

Releases (6 months)

Regular releases signal a project that ships; very frequent releases can also mean frequent updates on your side. n8n : 17. AutoGPT : 24. Edge: AutoGPT.

Last commit

A repository with no commit for months may fall behind new APIs and security fixes. n8n : October 24, 2026. AutoGPT : October 24, 2026. A tie on this point.

License

A clear open-source license (MIT, Apache…) allows commercial use and modification; without one, usage rights are unclear. n8n : no declared license. AutoGPT : no declared license. A tie on this point.

Self-hosting

Running the agent on your machine or server keeps your files and keys with you. n8n : yes. AutoGPT : yes. A tie on this point.

Supported models

An agent that accepts several model families lets you pick the best value, or a local model. n8n : 6. AutoGPT : 4. Edge: n8n.

Interfaces

Terminal, code editor, web app or chat: more interfaces mean more ways to fit it into your work. n8n : 3. AutoGPT : 1. Edge: n8n.

Risk level

Our risk level considers the access granted (terminal, files, network) and default human approval. n8n : moderate. AutoGPT : moderate. A tie on this point.

Community (forks)

Forks count developers who copied the project to adapt it: a sign of a living ecosystem. n8n : 61.2K. AutoGPT : 45.9K. Edge: n8n.

Track record

An older project has had time to fix early flaws; a recent one often brings the latest ideas. n8n : June 2019. AutoGPT : March 2023. Edge: n8n.

In charts

Our analysis

n8n describes visual workflows that connect applications, code and AI agents, either in the cloud or on your own server. AutoGPT describes specialized agents and visual workflows for carrying out tasks and automated routines. This suggests n8n may fit teams starting with a set of systems they need to connect. AutoGPT may appeal when the starting point is an agent assigned to a particular task. Those are interpretations of the descriptions, rather than evidence of different autonomy levels. n8n uses TypeScript and AutoGPT uses Python, a distinction that may influence how comfortably a technical team can work with each codebase.

Created on June 22, 2019, n8n has 208,491 GitHub stars and 61,222 forks. AutoGPT, created on March 16, 2023, has 187,725 stars and 45,894 forks. n8n records 14,403 commits over twelve months, compared with AutoGPT's 4,401. AutoGPT has more releases over six months, at 24 versus 17. Both show a latest commit dated October 24, 2026. Their scores of 85 and 84 out of 100 describe popularity, activity and framework, rather than quality. n8n lists Starter at €20 monthly, billed annually, with 2,500 monthly executions and agents included. No AutoGPT pricing is supplied, so a complete cost comparison is unavailable.

Both projects are described as open source and support self-hosting, but neither record specifies a license. You therefore cannot establish detailed reuse or redistribution rights from these records alone. Both have a medium risk classification for the same stated reason: missing license information. This is not evidence of a technical vulnerability. Self-hosting provides a deployment option, but does not by itself establish how information is handled when external models are involved. Neither record explains data retention or confidentiality arrangements. Human approval mechanisms are also unspecified, leaving an important operational question unresolved if your automation needs review before it performs actions.

n8n lists web, CLI and API interfaces, whereas AutoGPT lists a web interface only. n8n names Claude, GPT, Gemini, DeepSeek, local models and OpenRouter. AutoGPT names Claude, GPT, Llama and local models. These declared scopes may help you identify which project matches your existing setup, but they do not establish supported versions or integration depth. n8n's Starter execution allowance gives you a concrete planning constraint. AutoGPT's missing pricing leaves the financial side less defined. For either project, daily suitability will depend on your workflow structure and how you address the human approval arrangements that are not documented in the supplied data.

Depending on your situation

The right choice depends on use. For a few common situations, here are the criteria that matter and who wins (n8n value / AutoGPT value).

Trying it out quickly

Here, n8n has the edge: it wins 3 of the 3 criteria that matter in this situation, namely interfaces (3 / 1), supported models (6 / 4), and popularity (github stars) (208.5K / 187.7K).

Production use

Neither stands out on the criteria for this situation (activity over a year (14,403 commits / 4,401 commits), last commit (October 24, 2026 / October 24, 2026), license (no declared license / no declared license), and releases (6 months) (17 / 24)): decide with a trial.

Security and control

Neither stands out on the criteria for this situation (risk level (moderate / moderate) and self-hosting (yes / yes)): decide with a trial.

Which one to choose?

Choose n8n if…

• you value popularity (github stars) (208.5K)
• you value activity over a year (14,403 commits)
• you value supported models (6)
• you value interfaces (3)
• you value community (forks) (61.2K)

n8n is a logical option if you need to connect applications, code and agents through several access methods, including a CLI and an API. Its listed Gemini, DeepSeek and OpenRouter support may also match your requirements. The Starter plan provides a specific budget reference, provided its execution allowance and annual billing arrangement suit your expected usage.

Choose AutoGPT if…

• you value releases (6 months) (24)

AutoGPT may fit when your project centers on specialized agents and recurring automated tasks through a web interface. Python and listed Llama support may be relevant to your team. Self-hosting is available, but missing pricing and unspecified license terms mean you still need to establish the financial and reuse conditions before settling on a deployment approach.

Strengths and limits of each

n8n

• + Widely followed: 208.5K stars
• + Very active development
• + Frequent releases (17 in a year)
• − No licence declared

AutoGPT

• + Widely followed: 187.7K stars
• + Very active development
• + Frequent releases (29 in a year)
• − No licence declared

The best test is still yours: take three real tasks from your day and give them to both for a week. Our “Which AI agent?” quiz can also guide you.

What about the others?

If neither suits you, look at Langflow, Sim, Dify, Kestra, Trigger.dev, and Activepieces.

Related comparisons:

• n8n vs Make
• n8n vs Zapier
• Dify vs n8n
• AutoGPT vs Dify
• n8n vs Langflow

Conclusion

n8n offers a wider set of declared interfaces and a documented pricing reference. AutoGPT emphasizes specialized agents and records more releases over the past six months. Community statistics do not establish which produces better results. Choose according to your workflow design, models and access requirements. For both projects, the supplied information leaves reuse rights and human approval mechanisms unresolved, while AutoGPT's cost remains unspecified.