MLflow
Open-source AI engineering platform for agents, LLMs and ML models
Overall score
About
MLflow is the open-source platform for managing the AI/ML lifecycle, originally released by Databricks in 2018 and now used across more than 60 million monthly downloads. The current product spans classical ML (experiment tracking, model registry, deployment) and modern LLM and agent workflows (tracing, evaluation, prompt versioning). Self-host the framework for free under Apache 2.0, or use Managed MLflow billed through Databricks.
Best for: Engineering teams shipping LLM agents or production ML models who want open-source experiment tracking, evaluation and observability without paying for a closed MLOps SaaS.
Pricing
Open Source
- Monthly
- Free
- Annual /mo
- Free
- Billing
- flat
- Notes
- Full framework feature set;Apache 2.0 license;Self-hosted tracking server;Model registry;LLM tracing and evaluation;All integrations · Install via pip install mlflow; you operate the tracking backend and artifact store.
Managed MLflow (via Databricks)
- Monthly
- n/a
- Annual /mo
- n/a
- Billing
- usage_based
- Notes
- Fully managed tracking server;Model registry with Unity Catalog governance;LLM tracing and evaluation;Production agent monitoring;14-day Databricks trial with $400 in credits · Billed via per-second Databricks DBU consumption; rates vary by cloud provider and workload type.
| Tier | Monthly | Annual /mo | Billing | Notes |
|---|---|---|---|---|
| Open Source | Free | Free | flat | Full framework feature set;Apache 2.0 license;Self-hosted tracking server;Model registry;LLM tracing and evaluation;All integrations · Install via pip install mlflow; you operate the tracking backend and artifact store. |
| Managed MLflow (via Databricks) | n/a | n/a | usage_based | Fully managed tracking server;Model registry with Unity Catalog governance;LLM tracing and evaluation;Production agent monitoring;14-day Databricks trial with $400 in credits · Billed via per-second Databricks DBU consumption; rates vary by cloud provider and workload type. |
Key features
- Experiment tracking with parameters, metrics and artifacts
- Model registry with versioning and stage transitions
- LLM tracing and observability built on OpenTelemetry
- 50+ built-in LLM evaluation metrics plus LLM-as-a-judge
- Prompt versioning and optimization
- Model and agent deployment as REST APIs or batch inference
Integrations
Trust & compliance
- Stage range
- MVP → Growth
- Founded
- 2018
- Status
- active
- SOC 2
- unknown
- GDPR
- unknown
- Data residency
- customer_choice
- External rating
- n/a
- Last verified
- May 2026
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