AutoGPT Platform vs LangBot
Short answer
AutoGPT Platform: Visual builder for long-running AI agents and workflows, self-hostable as a single container. LangBot: Platform for AI chatbots on WeChat, WeCom, QQ, Feishu, DingTalk, Slack, Discord and Telegram, run from one dashboard. Both are in our AI app & agent builders category.
Choose AutoGPT Platform if you want: larger community (188k vs 18.7k GitHub stars) and simpler deploy (one container vs a multi-container stack).
Choose LangBot if you want: fewer license conditions (Permissive vs Source-available).
LangBot publishes no official RAM figure, so we cannot compare hosting cost directly.
Last updated · computed from each project's official docs and live GitHub data · sources
AutoGPT Platform vs LangBot side by side
| AutoGPT Platform | LangBot | |
|---|---|---|
| Category | AI app & agent builders | AI app & agent builders |
| What it is | Visual builder for long-running AI agents and workflows, self-hostable as a single container. | Platform for AI chatbots on WeChat, WeCom, QQ, Feishu, DingTalk, Slack, Discord and Telegram, run from one dashboard. |
| License | Polyform Shield 1.0.0 (autogpt_platform/); MIT for the rest | Apache-2.0 |
| License type | Source-available | Permissive |
| License conditions | The platform code in autogpt_platform/ is under the Polyform Shield License: use and modification for your business are allowed, but you may not use it to offer a product or service that competes with AutoGPT. The classic agent, Forge and benchmark outside that folder are MIT. | Permissive. Internal and commercial use allowed; keep license and notices. |
| Status | Active | Active |
| GitHub stars | 188k | 18.7k |
| Last commit | Nov 4, 2026 | Nov 4, 2026 |
| Latest release | autogpt-platform-beta-v0.11.0 | v4.11.4 |
| Minimum hardware | 6 GB RAM | Not published |
| Recommended hardware | Not published | Not published |
| RAM measured by us | Not tested yet | Not tested yet |
| GPU | Not required / not stated | Not required / not stated |
| Est. server cost | from €35.99/mo | Not estimated |
| Deploy method | Docker (single container) | Docker Compose |
| Known gotchas | 4 listed | 4 listed |
| Telemetry | Not documented | On by default |
| Calls home by default | Not documented | Yes, by default |
| SSO (OIDC / SAML / LDAP) | Not documented | Not documented |
| Audit log | Not documented | Not documented |
| RBAC | Not documented | Yes, free |
| Details | Full AutoGPT Platform guide → | Full LangBot guide → |
Key differences
- License: AutoGPT Platform: Polyform Shield 1.0.0 (autogpt_platform/); MIT for the rest (Source-available). LangBot: Apache-2.0 (Permissive).
- Official hardware: AutoGPT Platform: minimum 6 GB RAM. LangBot: not published.
- Est. server cost: AutoGPT Platform: from €35.99/mo. LangBot: not estimated (no official RAM figure).
- Deploy: AutoGPT Platform: Docker (single container) · single container. LangBot: Docker Compose · multi-container stack.
- GitHub stars: AutoGPT Platform: 188k. LangBot: 18.7k.
- Latest release: AutoGPT Platform: autogpt-platform-beta-v0.11.0 (Nov 4, 2026). LangBot: v4.11.4 (Oct 29, 2026).
Same for both: Category: AI app & agent builders; GPU: not required or not stated; Status: Active; Last commit: Nov 4, 2026.
AutoGPT Platform vs LangBot: FAQ
AutoGPT Platform or LangBot: which should a small business choose?
Choose AutoGPT Platform if you want: larger community (188k vs 18.7k GitHub stars) and simpler deploy (one container vs a multi-container stack). Choose LangBot if you want: fewer license conditions (Permissive vs Source-available). LangBot publishes no official RAM figure, so we cannot compare hosting cost directly.
Which is cheaper to self-host, AutoGPT Platform or LangBot?
AutoGPT Platform: from €35.99/mo. LangBot: not estimated (no official RAM figure). Our estimate is the cheapest Hetzner Cloud plan that meets each project's official RAM and vCPU figure; it covers the server only.
How much hardware do AutoGPT Platform and LangBot need?
AutoGPT Platform: minimum 6 GB RAM. LangBot: not published.
What is the license difference between AutoGPT Platform and LangBot?
AutoGPT Platform: Polyform Shield 1.0.0 (autogpt_platform/); MIT for the rest (Source-available). The platform code in autogpt_platform/ is under the Polyform Shield License: use and modification for your business are allowed, but you may not use it to offer a product or service that competes with AutoGPT. The classic agent, Forge and benchmark outside that folder are MIT. LangBot: Apache-2.0 (Permissive). Permissive. Internal and commercial use allowed; keep license and notices. This is a summary, not legal advice.
Is AutoGPT Platform or LangBot more actively maintained?
AutoGPT Platform: Active, last commit Nov 4, 2026. LangBot: Active, last commit Nov 4, 2026. GitHub data refreshed Nov 4, 2026.
Which is easier to deploy, AutoGPT Platform or LangBot?
AutoGPT Platform installs via Docker (single container) (single container); LangBot via Docker Compose (multi-container stack). AutoGPT Platform lists 4 known gotchas and LangBot lists 4; see each app page.
Related
- AutoGPT Platform self-hosting guide · LangBot self-hosting guide
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- Add a third app in the interactive comparison
Sources
- AutoGPT Platform GitHub repository: github.com/Significant-Gravitas/AutoGPT
- AutoGPT Platform documentation, AutoGPT Platform hardware requirements: agpt.co/docs/platform/self-hosting/single-container
- AutoGPT Platform license: github.com/Significant-Gravitas/AutoGPT/blob/master/LICENSE
- AutoGPT Platform deploy instructions: github.com/Significant-Gravitas/AutoGPT#self-host-autogpt
- LangBot GitHub repository: github.com/langbot-app/LangBot
- LangBot documentation, LangBot hardware requirements, LangBot deploy instructions: langbot.app/docs/en/deploy/langbot/docker
- LangBot license: github.com/langbot-app/LangBot/blob/master/LICENSE
- Hetzner Cloud pricing used for cost estimates (read 2026-11-01): www.hetzner.com/cloud/regular-performance
- GitHub REST API (stars, commits, releases): docs.github.com/en/rest
Every value is generated from the same verified data as the app pages. Spotted something wrong? Tell us.