Price checkPer free self-hosted
Open Source (self-hosted)FreeManaged MLflow (Databricks)Custom
See all 2 plans

All MLflow Plans & Pricing

Plan Monthly Annual Best For
View all features by plan (compare side-by-side)

Open Source (self-hosted)

  • 100% open source under the Apache 2.0 license
  • Experiment tracking, model registry, and evaluation
  • Tracing and observability for agents and LLM apps
  • Unlimited users — no license fees ever
  • You provide and pay for your own compute, storage, and database

Managed MLflow (Databricks)

  • Fully managed MLflow built into the Databricks platform
  • Billed via Databricks compute consumption — no separate MLflow list price
  • Enterprise security, scaling, and support from Databricks
  • Free trial available through Databricks
Try MLflow Free
Compare MLflow with alternativesAdjust seats, lock a tier, add up to 2 more products side-by-side. Shareable URL.
Quick Answer
Last verified:
High confidence

MLflow uses custom pricing as of July 2026 with 2 plans available. Contact MLflow directly for a personalized quote. Plan: Open Source (self-hosted) (free). Enterprise pricing is available on request. Pricing depends on your chosen tier, contract length, and negotiated discounts.

Use the interactive pricing calculator to estimate your exact cost based on team size and requirements.

  • Free tier: Yes

MLflow offers 2 pricing tiers: Open Source (self-hosted), Managed MLflow (Databricks). The Managed MLflow (Databricks) plan is teams already on (or moving to) databricks who want mlflow without running infrastructure.

Compared to other mlops platforms software, MLflow is positioned at the budget-friendly price point.

  • 9 documented hidden costs beyond list price
Last verified: | Sources: 1 pricing pages and reviews

How much does MLflow cost?

MLflow uses custom pricing across 2 plans. Contact MLflow directly for a personalized quote. Plans include Open Source (self-hosted) (free), Managed MLflow (Databricks) (custom pricing).

MLflow Pricing Overview

MLflow uses custom pricing — contact their sales team for a quote. The Open Source (self-hosted) plan is free and is best for teams comfortable running their own tracking server who want zero license cost. The Managed MLflow (Databricks) plan requires contacting sales for a custom quote and is designed for teams already on (or moving to) databricks who want mlflow without running infrastructure.

There are at least 9 documented hidden costs beyond MLflow's list price, including implementation, training, and add-on fees.

This pricing was last verified in June 11, 2026 from 1 independent source.

Try MLflow Free
MLflow is an open-source AI engineering platform for tracking experiments, registering models, evaluating LLM applications, and tracing agents. The software itself is 100% open source under the Apache 2.0 license — MLflow's site describes it as "forever free, no strings attached" — so a self-hosted deployment has no license cost; you pay only for the infrastructure you run it on (tracking server, artifact storage, database). For teams that don't want to operate that infrastructure, Managed MLflow is offered as part of the Databricks platform. Databricks publishes no separate list price for Managed MLflow: it is billed through normal Databricks platform consumption (compute usage), and a free trial is available through Databricks. Budgeting for MLflow is therefore really a build-vs-buy question — self-hosting trades engineering time for zero license fees, while the managed offering folds MLflow's cost into your overall Databricks bill.

How MLflow Pricing Compares

Compare MLflow pricing against top alternatives in MLOps Platforms.

ClearML $0-$15/mo View pricing → Comet ML $0-$19/mo View pricing → Determined AI Free View pricing →

Compare MLflow vs Alternatives

Before committing to MLflow, compare pricing with these 3 alternatives in the same category.

VSClearML
Free

Small teams and individual researchers, or any team using the free open-source self-hosted version

Compare pricing
VSComet ML
Free

Individuals and small teams getting started with LLM observability and evaluation

Compare pricing
VSDetermined AI
Custom

ML teams and research organizations self-hosting on their own GPU infrastructure

Compare pricing

All MLflow alternatives & migration guides

What Companies Actually Pay for MLflow

Review scores
Third-party review aggregates, as of Jul 2026
Top pricing complaints
Steep Learning Curve and Setup ComplexityPerformance IssuesLimited Collaboration and Multi-User SupportOverhead for Small Projects

How MLflow Pricing Compares

Software Starting Price Top Price
MLflow Custom Custom
Comet ML Free $19/month
ClearML Free $15/month
Determined AI Custom Custom
Neptune.ai $150/month $250/month
Weights & Biases Free $60/month

Browse all MLOps Platforms pricing →

9 MLflow Hidden Costs Beyond the List Price

Beyond the listed price, MLflow has at least 9 documented hidden costs that can significantly increase total cost of ownership.

Watch for 9 hidden costs
  • Compute Resources $0.36 per hour
    high 1 source
    industry "These costs are based on the size of the tracking server and its running duration."
  • Storage Costs $0.11 per GB per month
    medium 1 source
    industry "Amazon SageMaker with MLflow charges $0.11 per GB per month for storage."
  • Data Transfer/Egress Fees
    high 1 source
    industry "Data Transfer/Egress: Moving data between availability zones or out of a cloud provider can incur significant egress fees."
  • Underlying Cloud Infrastructure 50-70%
    critical 1 source
    industry "These infrastructure costs can account for 50-70% of the total Databricks spend."
  • Setup Complexity
    high 1 source
    industry "Operational Overhead and "Hidden" Costs of Open Source: * Setup Complexity: While open-source MLflow is "free" in terms of licensing, setting up a production-ready instance requires significant infrastructure changes, remote servers, and careful c..."
  • Maintenance and Engineering Time $200-500/month
    high 1 source
    industry "A self-hosted MLflow tracking server can cost an additional 10-20 hours/month in engineering time for maintenance, on top of server costs of $200-500/month."
  • Scaling Friction
    medium 1 source
    industry "Scaling Friction: What works for a small team can break at scale, leading to increased manual processes and a need for more robust solutions."
  • Security Gaps
    high 1 source
    industry "Security Gaps: Open-source MLflow, even with authentication enabled, may lack enterprise-grade features like audit trails, project isolation, and granular permissions, necessitating custom development or additional tooling."
  • Lack of Collaboration Features
    medium 1 source
    industry "Lack of Collaboration Features: MLflow's open-source version lacks built-in commenting, approval workflows, and team collaboration features, which can lead to inefficiencies and reliance on external tools like Slack and spreadsheets for model depl..."
Tip

Ask your MLflow sales rep about these costs upfront. Getting them in writing before signing can save you from surprise charges later.

Full hidden costs breakdown →

Intelligence sourced from 1 independent sources
industry
Key claims include inline source attribution. Data verified against multiple independent sources. 9 source citations total.

MLflow Contract Terms

MLflow contracts do not auto-renew. Changes require advance notice. These terms are sourced from verified buyer experiences.

Contract Terms
Auto-Renewal No

MLflow Pricing FAQ

01 Is MLflow free?

Yes. MLflow is 100% open source under the Apache 2.0 license, with no paid edition of the software itself. Self-hosting it costs nothing in license fees — your only costs are the infrastructure you run it on, such as the tracking server, artifact storage, and backing database.

02 How much does Managed MLflow on Databricks cost?

Databricks publishes no separate list price for Managed MLflow. It is part of the Databricks platform and billed through normal platform consumption (compute usage), so the cost depends entirely on your Databricks workloads. A free trial is available through Databricks.

03 What is the difference between open-source MLflow and Managed MLflow?

The core software is the same — Managed MLflow is built on open-source MLflow. The managed version removes the operational work (hosting, scaling, upgrades, security) and integrates with the rest of the Databricks workspace, while self-hosting gives you full control and no platform dependency.

04 Does MLflow charge per user or per model?

No. The open-source platform has no per-user, per-model, or per-experiment charges — it is free for unlimited users. On the managed side, Databricks bills by platform consumption rather than MLflow-specific units.

Is this pricing incorrect? — we'll verify and update it.