Langfuse vs Open-WebUI
| Tagline | Open-source LLM observability and evaluation platform for tracing AI application calls | Feature-rich self-hosted chat UI for Ollama and OpenAI-compatible APIs |
| Category | AI & LLM Tools | AI & LLM Tools |
| Replaces | OpenAI API | ChatGPT, OpenAI API |
| GitHub stars | 10k | 143k |
| Language | TypeScript | Docker |
| License | MIT | BSD-3-Clause |
| Self-host difficulty | 3/5 Moderate | 2/5 Easy |
| Deploy options | Docker Compose Kubernetes | Docker Docker Compose |
| Managed hosting | ||
| Last updated | 1 month ago | 8 days ago |
| View repo | View repo |
Where each falls short
The honest trade-offs — what you give up with each, versus the proprietary tools they replace.
Langfuse
- Some advanced evaluation and annotation features are cloud-only
- ClickHouse dependency adds significant infrastructure overhead
- No built-in alerting or on-call integrations
Open-WebUI
- Advanced reasoning models and GPT-4o-level capabilities depend entirely on the underlying model quality
- No native mobile app; browser-only experience
- Enterprise SSO/SAML and audit logging require additional configuration
- Plugin/tool ecosystem is smaller and less mature than ChatGPT's GPT store
Bottom line
Choose Open-WebUI if you want the lower-effort setup; choose Open-WebUI for the larger community and ecosystem. Open-WebUI has seen more recent development. Open each guide below for deploy steps and the full feature gap.
Langfuse
Open-source LLM observability and evaluation platform for tracing AI application calls