MLflow

Open source

Open source platform for tracking ML experiments, packaging models, and managing model registries.

by LF AI & Data FoundationOfficial site ↗Source code ↗

Pricing: free
Free tier: true
License: open-source
Open source: Yes

Editorial review

MLflow has not yet been editorially reviewed. User reviews and published field data below are unaffected — we say so rather than implying an editorial verdict.

Facts & attributes

Every value carries its evidence state. “—” means unknown — never a silent default (P-02).

Identity · Taxonomy

Documentation(HTTPS URL): https://mlflow.org/docs/latest/Verified
Tags(open-source;cloud-native): experiment tracking, MLOps, LLMOps, open source, AI engineeringVerified

Platform · Deployment

Delivery model(SaaS;self-hosted;desktop;mobile;embedded;managed-cloud;appliance): self-hostedVerification pending

Pricing · Licensing

Free plan(true/false): trueVerification pending
License model(proprietary;open-source;source-available;dual-license): open-sourceVerified
Pricing model(free;subscription;usage;seat;asset;transaction;revenue-share;perpetual;custom): freeVerified
Source repository(HTTPS URL): https://github.com/mlflow/mlflowVerified
SPDX license IDs(Apache-2.0;MIT): Apache-2.0Verification pending

Features · Product · Fit

Core capabilities(authoring;automation;analytics): Experiment tracking, Observability with production-grade tracing, Model evaluation with 50+ built-in metrics and LLM judges, Prompt registry and prompt optimization, AI Gateway for LLM providers, Model Registry & deploymentVerification pending

Api · Integrations · Ecosystem

API available(true/false): trueVerification pending
CLI(true/false): trueVerification pending

Audience · Use · Case

Best for(Neutral editorial summary): Teams wanting a free, open-source platform for experiment tracking, LLM observability, and model lifecycle management with no vendor lock-inVerification pending
Company-size fit(individual;SMB;mid-market;enterprise): individual, SMB, mid-market, enterpriseVerification pending
Primary use cases(build;monitor;automate): Debugging, evaluating, and monitoring LLM applications and agents, Machine learning and deep learning model lifecycle managementVerification pending
Skill level(beginner;intermediate;advanced;specialist): intermediateVerification pending

Lifecycle · Versioning

Current version(1.12.3): 3.17.2Verified
Maintenance status(active;maintenance;deprecated;EOL;archived): activeVerified

Vendor · Maintainer

Vendor type(commercial;foundation;community;government;consortium;individual): foundationVerified

Also categorized in

MLOps Platforms

User reviews

Review policy

No published reviews yet.