Registry › Compare › MLflow vs OpenLLMetry

MLflow vs OpenLLMetry

Both are Grade A and 3.1 points apart, so choose on what you weigh most. MLflow leads on maintenance and adoption, and rests on broader evidence; OpenLLMetry leads on transparency.

A MLflow 89.6

The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.

mlflow/mlflow · #28 overall · #2 Observability & Evaluation · coverage A (4/5)

Choose MLflow if maintenance and adoption matter most.

+3.1Maintenance: last push today, against 2d ago
+2.8Adoption: 4.7M weekly downloads against 458.6k
A vs BEvidence coverage: 4 of 5 independent signal types, against 3

A OpenLLMetry 86.5

Open-source observability for your GenAI or LLM application, based on OpenTelemetry

traceloop/openllmetry · #75 overall · #4 Observability & Evaluation · coverage B (3/5)

Choose OpenLLMetry if transparency matters most.

+0.8Transparency: OSSF Scorecard 6.5 against 5.5

Where they differ

19.4

Safety / IntegrityOpenLLMetry +0.3

19.7

13.2

TransparencyOpenLLMetry +0.8

14.0

20.0

MaintenanceMLflow +3.1

16.9

19.6

AdoptionMLflow +2.8

16.8

-0.6

Runtime calibrationOpenLLMetry +1.7

+1.1

1 dimension identical: Identity 18.0 · Full evidence table

An independent, evidence-based trust comparison of MLflow and OpenLLMetry, 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	MLflowmlflow/mlflow	OpenLLMetrytraceloop/openllmetry
HVTrust score	89.6	86.5
Evidence grade	A	A
Coverage grade	A	B
Overall rank	#28	#75
Rank in Observability & Evaluation	#2	#4
GitHub stars	28.5k	7.5k
Last updated	today	2d ago
Build provenance	Yes	Yes
OSSF Scorecard	5.5 / 10	6.5 / 10
License	Apache-2.0	Apache-2.0
Downloads	4.7M/wk	459k/wk
Trust dimensions (points earned)
Safety / integrity / 25	19.4	19.7
Identity & provenance / 18	18.0	18.0
Transparency / 17	13.2	14.0
Maintenance / 20	20.0	16.9
Adoption / 20	19.6	16.8
Runtime capability surface (full matrix)
MCP server	Implemented	Implemented
External providers	3 — Amazon Bedrock, Anthropic, Postgres	9 — Amazon Bedrock, Anthropic, Cohere, …
Requires API keys	No	No
Plugin surface	plugins	—
Provenance drift	Unknown	Match

Open in the live compare tool → MLflow profile OpenLLMetry 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 →