Best Open-Source Observability & Evaluation: Weights & Biases Weave vs Langfuse
A data-backed comparison of the top two observability & evaluation on HVTracker, built from public trust signals rather than stars alone.
Short answer: Weights & Biases Weave currently leads Langfuse on HVTracker's evidence-weighted trust score: 84.9 vs 74.7/100. This is not a popularity ranking; it combines supply-chain safety, identity/provenance, transparency, maintenance, and adoption signals.
Weights & Biases Weave
Weave is a toolkit for developing AI-powered applications, built by Weights & Biases.
Langfuse
🪢 Open source LLM engineering platform: LLM Observability, metrics, evals, prompt management, playground, datasets. Inte
Weights & Biases Weave vs Langfuse: trust signal breakdown
Both projects are tracked in the Observability & Evaluation category, but they do not expose the same evidence. The table below compares the public signals that feed HVTrust.
| Signal | Weights & Biases Weave | Langfuse |
|---|---|---|
| HVTrust score | 84.9 | 74.7 |
| Safety / Integrity | 22.6/30 | 16.1/30 |
| Identity / Provenance | 20.0/20 | 12.0/20 |
| Transparency | 15.2/20 | 16.8/20 |
| Maintenance | 19.9/20 | 20.0/20 |
| Adoption | 7.2/10 | 9.8/10 |
| OSSF Scorecard | 5.2 | 6.8 |
| Signed commits | 96% | 99% |
| Package provenance | Verified | Not detected |
Which one should you evaluate first?
If your priority is the most verifiable trust profile today, start with Weights & Biases Weave. It has the stronger current HVTrust score and ranks higher in Observability & Evaluation. If your use case depends on a specific runtime, language, license, or integration model, use the individual profiles rather than the headline score alone.
For production use, the practical checklist is: inspect the security policy, confirm package provenance or release signing where available, review recent maintenance cadence, and compare the exact trust breakdown. HVTracker is meant to reduce the first-pass research burden, not replace your own risk review.