Open source AI engineering platform. Debug, analyze and iterate together.
Langfuse vs litellm
Developer ecosystem comparison across GitHub activity, SDKs, documentation, community, reach and momentum.
Langfuse (Open source AI engineering platform. Debug, analyze and iterate together.) and litellm both appear on the Smoower Developer Ecosystem Index.
Langfuse (rank #63) holds a meaningful lead over litellm (rank #1114) on the overall Smoower ecosystem score (59 vs 7). The gap of 52 points reflects composite signals across code, docs, community and reach.
On code quality (the state of repositories, tests, releases and polish), Langfuse is clearly ahead of litellm. On education (docs, guides and learning material for developers), Langfuse is clearly ahead of litellm. On community (issue response, PR reviews and discussion health), Langfuse is clearly ahead of litellm. On reach (how visible the ecosystem is beyond its own repos), Langfuse is clearly ahead of litellm. On momentum (release cadence and how fast the ecosystem moves), Langfuse is clearly ahead of litellm.
Langfuse carries 32,648 GitHub stars across 25 public repos, with 22 repositories active in the last 90 days and 147 external contributors on record. litellm shows 0 stars across 0 public repos, 0 active in the last 90 days and 0 external contributors.
Langfuse is the stronger read for anyone weighting code quality. litellm makes more sense for teams already using its adjacent tools. The table below breaks the scores down pillar by pillar; the linked profiles cover the underlying repos, docs and community signals in full.
Side-by-side metrics
| Metric | Langfuse | litellm |
|---|---|---|
| Ranking | ||
| Overall rank | #63 | #1114 |
| Pillars | ||
| Overall | 59 | 7 |
| Code | 56 | 0 |
| Education | 50 | 0 |
| Community | 53 | 0 |
| Reach | 71 | 40 |
| Momentum | 54 | 0 |
| Builder experience | 0 | 0 |
| Signals | ||
| Stars | 32,648 | 0 |
| Forks | 4,263 | 0 |
| Public repos | 25 | 0 |
| Active repos (90d) | 22 | 0 |
| External contributors | 147 | 0 |
| Avg polish | 60 | 0 |
| Avg AI-readiness | 41 | 0 |