Langflow vs AutoGPT
Two of the top agent platforms, side by side: score, setup, license, activity and what each review found.
Langflow
Visual flow builder that deploys agents as APIs or MCP servers
AutoGPT
Block-based builder for agents that run on demand, schedule or trigger
| What we compare | Langflow | AutoGPT |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 87, widely used | 99, widely used |
| Freshness | 100, active | 100, active |
| Maintenance | 91, healthy | 79, fair |
| Easy to run | 33, some setup | 17, hard |
| Agent-ready | 70, partly | 85, ready |
| Facts from GitHub and the README | ||
| Stars | 155.5k | 187.5k |
| License | MIT (permissive) | custom license (read the license) |
| Last commit | Oct 2026 | Oct 2026 |
| Last release | Oct 2026 | Oct 2026 |
| Language | Python | Not stated |
| Docker | Yes | No |
| GPU | Not needed | Not needed |
| arm64 or Apple Silicon | Not stated | Mentioned |
Langflow
Langflow is a Python 3.10 to 3.14 visual builder (uv pip install langflow, or the langflowai/langflow Docker image on port 7860) for agents and LLM workflows. Every component is editable Python, flows run in an interactive playground, and a finished flow can be served as an API, exported as JSON for Python apps or exposed as an MCP server. Multi-agent orchestration and LangSmith or LangFuse tracing are built in.
Who it is for: Developers prototyping agent flows who want Python under the hood
Strengths
- Any flow becomes an API endpoint or an MCP server for MCP clients
- Component source is Python you can edit inside the builder
- One container on port 7860; no other service in the quick start
- MIT license; desktop builds for Windows and macOS
Weaknesses
- README names no model providers, vector stores or resource needs
- No root Dockerfile or compose file; container config lives in the docs
- Enterprise-ready claim is not detailed in the README
- no GPU
- Docker + Compose
- port 7860
AutoGPT
AutoGPT Platform lets you describe a job in plain English (AutoPilot) or wire blocks on a visual canvas, then run the agent on demand, on a schedule or from a trigger, with a dashboard of runs and costs and a marketplace of shared agents. It connects to 45+ platforms such as Gmail, Slack, GitHub and Notion. Self-hosting is free with your own Docker host and model API keys; the hosted platform is paid.
Who it is for: Non-developers and teams wanting scheduled agents over SaaS tools
Strengths
- Plain-English AutoPilot and a drag-and-connect block builder for the same agent
- Agents run on demand, on schedules or from triggers with a run and cost dashboard
- 45+ integrations including Gmail, Google Sheets, GitHub, Slack, Notion, Jira, Salesforce
- Classic standalone agent still shipped under MIT in classic/
Weaknesses
- Platform code is Polyform Shield: no offering it as a competing hosted service
- README has no self-host commands; the single-container installer is still unreleased
- Windows self-hosting is manual-guide only
- Hosted platform charges per agent run; README is largely marketing
- no GPU
- Needs Docker