Registry › Compare › Langfuse vs Weights & Biases Weave

Langfuse vs Weights & Biases Weave

Weights & Biases Weave leads on trust: 83.8/100 (Grade A) against 79.9/100 (Grade B), a 3.9-point gap. Langfuse leads on maintenance and adoption; Weights & Biases Weave leads on supply-chain integrity and provenance.

B Langfuse 79.9

🪢 Open source AI engineering platform: AI Gateway, agent observability, evals, and prompt/skill management, built on OpenTelemetry. One open platform for every AI call and every agent. Self-host or use Langfuse Cloud.

langfuse/langfuse · #196 overall · #6 Observability & Evaluation · coverage A (4/5)

Choose Langfuse if maintenance and adoption matter most.

+5.2Adoption: 10.0M weekly downloads against 388.1k
+1.5Maintenance: last push 1d ago, against 2d ago
+0.9Transparency: OSSF Scorecard 7.4 against 6.4

A Weights & Biases Weave 83.8

Weave is a toolkit for developing AI-powered applications, built by Weights & Biases.

wandb/weave · #118 overall · #5 Observability & Evaluation · coverage A (4/5)

Choose Weights & Biases Weave if supply-chain integrity and provenance matter most.

+7.2Identity / Provenance: package provenance attested, against none
+5.5Safety / Integrity: package provenance attested, against none

Where they differ

14.2

Safety / IntegrityWeights & Biases Weave +5.5

19.7

10.8

Identity / ProvenanceWeights & Biases Weave +7.2

18.0

14.8

TransparencyLangfuse +0.9

13.9

19.9

MaintenanceLangfuse +1.5

18.4

20.0

AdoptionLangfuse +5.2

14.8

+0.2

Runtime calibrationLangfuse +1.2

-1.0

Full evidence table

An independent, evidence-based trust comparison of Langfuse and Weights & Biases Weave, two Observability & Evaluation projects in the HVTracker registry. Scores come from public, checkable signals — supply-chain provenance, OSSF Scorecard, maintenance, and adoption — not popularity.

Full evidence

Signal	Langfuselangfuse/langfuse	Weights & Biases Weavewandb/weave
HVTrust score	79.9	83.8
Evidence grade	B	A
Coverage grade	A	A
Overall rank	#196	#118
Rank in Observability & Evaluation	#6	#5
GitHub stars	37.4k	1.1k
Last updated	1d ago	2d ago
Build provenance	No	Yes
OSSF Scorecard	7.4 / 10	6.4 / 10
License	NOASSERTION	Apache-2.0
Downloads	10.0M/wk	388k/wk
Trust dimensions (points earned)
Safety / integrity / 25	14.2	19.7
Identity & provenance / 18	10.8	18.0
Transparency / 17	14.8	13.9
Maintenance / 20	19.9	18.4
Adoption / 20	20.0	14.8
Runtime capability surface (full matrix)
MCP server	Implemented	Implemented
External providers	2 — Anthropic, OpenAI	8 — Amazon Bedrock, Anthropic, Cohere, …
Requires API keys	Yes	Yes
Plugin surface	plugins	—
Provenance drift	Unknown	Partial

Open in the live compare tool → Langfuse profile Weights & Biases Weave profile More Observability & Evaluation →

How to read this: HVTrust (0–100) weighs supply-chain signals (provenance, OSSF Scorecard, signed commits, open license) alongside real-world adoption, scaled by an evidence-confidence factor. Grade bands: A ≥ 80, B ≥ 65, C ≥ 50, D < 50. Signals refresh daily. Full methodology v4.4 →