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Project comparison
Evidently vs MLflow
Compare adoption, momentum, maintenance health, and project basics before choosing which tool to evaluate deeper.
Evidently
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
Best matched with other platform tools.
8.0K
Stars
+71
Weekly
54/100
Health
MLflow
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.
Best matched with other platform tools.
25.9K
Stars
+129
Weekly
81/100
Health
Quick Take
Adoption
MLflow has the larger GitHub footprint with 25.9K stars.
Momentum
MLflow is currently growing faster at +129 stars this week.
Maintenance
MLflow has the stronger automated maintenance signal at 81/100. This is not a security or fit verdict.
Side-by-side evidence
Use these signals to narrow your choice, then confirm setup, license, and fit upstream.
| Signal | Evidently | MLflow |
|---|---|---|
| Evidence status | Basic listing· 2026-10-04 09:18 UTC | Basic listing· 2026-10-04 09:17 UTC |
| GitHub stars | 8.0K | 25.9K |
| Weekly growth | +71 | +129 |
| Health score | Watch54/100 | Strong81/100 |
| Contributors | 97 | 1.0K |
| Commits per week | 0.2 | 112.2 |
| Open issues | 323 | 2.1K |
| Language | Jupyter Notebook | Python |
| License | Apache-2.0 | Apache-2.0 |
| Last commit | 2026-09-29 08:32 UTC | 2026-05-11 23:04 UTC |
| Last release | v0.7.23 | v3.12.0 |
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