coding

ClearML

Open-source MLOps platform for tracking experiments, storing artifacts and managing AI infrastructure.

How the 7.6 was reached

  1. Quality of output7/10

    6,895 GitHub stars, active project with a recent push, Apache-2.0, and 2,100+ organizations claimed; adoption is solid but not tens of thousands of stars. github.com

  2. Ease of use7/10

    Vendor says sign-up takes under 2 minutes and a free tier needs no card; docs exist, but there are no independent usability reports. github.com

  3. Pricing value9/10

    Free Community tier with 100GB artifact storage and Apache-2.0 open-source code; Pro is $15 per user per month. clear.ml

  4. API and integration quality8/10

    Open-source Python library with a 2-line integration and a documented docs site. clear.ml

  5. Solves the problem it claims to solve7/10

    Active open-source MLOps platform with 6,895 stars and 802 forks supports the infrastructure claim; there are no independent reviews of the enterprise-scale claim. github.com

7.6/10 is the mean of the 5 criteria that apply. Scored on the five-criteria rubric v1, 29 September 2026. How scoring works

Pricing

Community
Free
  • 100GB artifact storage
  • 1GB metric events
  • 1M API calls/month
  • No credit card required
Pro
$15 per user/month
  • 120GB artifact storage
  • 2M API calls/month
Usage add-ons
Pay as you go
  • $0.1/1GB artifact storage
  • $0.01/1MB metric events
  • $1/100K API calls
  • $0.04/hr per Application

Key Features

  • Open-source Python library with 2-line integration
  • Infrastructure control plane
  • AI development center
  • GenAI app engine
  • GPU-as-a-Service for enterprises

Pros & Cons

Pros

  • Free Community tier and Apache-2.0 open-source code
  • Pro is $15 per user/month
  • 6,895 GitHub stars and an active project
  • Documented docs site

Cons

  • Adoption is solid but far below the biggest ML projects
  • No independent usability reports
  • Enterprise-scale claim has no independent reviews
  • Usage add-ons make costs harder to predict
Verdict

ClearML suits ML teams that want an open-source, self-hostable tracking and orchestration stack with a cheap paid tier. Teams wanting proof of enterprise scale should ask for references. A good 7.6.

Try ClearML →

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