All ClearML Plans & Pricing

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

Community

  • Up to 3 users
  • 100 GB artifact storage
  • 1M API calls/month
  • Experiment tracking
  • Data versioning
  • Model repository
  • Community support
  • Open-source self-hosting option (unlimited users)

Pro

  • Up to 10 users
  • 120 GB artifact storage
  • 1.2M API calls/month
  • Cloud autoscaling
  • Hyperparameter optimization
  • Pipeline automation
  • Email support
  • Advanced dashboards

Scale

  • Unlimited users
  • Large artifact storage
  • High API call limits
  • Advanced infrastructure management
  • Priority support
  • Custom SLAs

Enterprise

  • Everything in Scale
  • Security integrations (SSO, RBAC)
  • Dedicated support
  • On-premises or private cloud deployment
  • GPU-as-a-service options
  • Compliance and audit logs
  • Custom contract terms
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Cost calculator

What does ClearML actually cost you?

Drag the slider. Pick a tier. Your projected spend updates as you go.

Tier
Billing
Your projected cost$375per month · $15/unit × 25units
Year 1 license$4.5K12 months at this rate
At a glance

List price by tier (annualized, per unit)

Per-unit list price across ClearML's plans, annualized. Custom-priced tiers show a hatched bar.

CommunityCustom
Pro$180/yr
ScaleCustom
EnterpriseCustom
Quick Answer
Last verified:
Estimate

ClearML costs Free to $15 per month as of July 2026, with 4 plans available including a free tier. Plans: Community (free), and Pro at $15/month. 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

ClearML offers 4 pricing tiers: Community, Pro, Scale, Enterprise. A free plan is available. Paid plans include Pro at $15/per user/month. The Pro plan is ml teams that need managed cloud autoscaling and pipeline automation beyond the free tier.

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

  • 13 documented hidden costs beyond list price
  • G2 rating: 4.7 out of 5 from 13 reviews (as of Jul 2026)

How much does ClearML cost?

ClearML offers 4 pricing plans, starting with a free tier and scaling to custom enterprise pricing. Plans include Community (free), Pro at $15/month, Scale (custom pricing), Enterprise (custom pricing).

ClearML Pricing Overview

ClearML has 4 pricing plans, including a free tier. Paid plans range from $0 to $15/month. The Community plan is free and is best for small teams and individual researchers, or any team using the free open-source self-hosted version. The Pro plan costs $15/month, best for ml teams that need managed cloud autoscaling and pipeline automation beyond the free tier. The Scale plan requires contacting sales for a custom quote and is designed for organizations running large-scale ai pipelines requiring advanced infrastructure control. The Enterprise plan requires contacting sales for a custom quote and is designed for large enterprises requiring on-premises deployment, compliance, and dedicated support.

There are at least 13 documented hidden costs beyond ClearML's list price, including implementation, training, and add-on fees.

This pricing was last verified in May 5, 2026 from 1 independent source.

ClearML is an open-source MLOps platform providing experiment tracking, data versioning, model registry, pipeline orchestration, and GPU infrastructure management in one suite. It offers a free Community plan (up to 3 users), a Pro plan at $15/user/month (up to 10 users), and custom Scale and Enterprise plans for larger AI infrastructure needs.

How ClearML Pricing Compares

Compare ClearML pricing against top alternatives in MLOps Platforms.

Compare ClearML vs Alternatives

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

All ClearML alternatives & migration guides

What Companies Actually Pay for ClearML

Review scores
G2 4.7out of 5 (13)
Third-party review aggregates, as of Jul 2026
Top pricing complaints
Complex Initial SetupLack of a User-Friendly InterfaceIntegration ChallengesLimited Language Support

How ClearML Pricing Compares

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

13 ClearML Hidden Costs Beyond the List Price

Beyond the listed price, ClearML has at least 13 documented hidden costs that can significantly increase total cost of ownership.

Watch for 13 hidden costs
  • Infrastructure Costs
    high 1 source
    industry "Community Plan: This is a free, open-source tier that can be self-hosted (unlimited users) or used as a free hosted SaaS tier (limited to 3 users, 100GB artifact storage, 1M API calls/month)."
  • Usage-Based Overages $0.10 per GB for artifact storage, $0.01 per MB for metric events, $1 per 100K API calls, and $0.04 per application hour
    high 1 source
    industry "For instance, overage rates are approximately $0.10 per GB for artifact storage, $0.01 per MB for metric events, $1 per 100K API calls, and $0.04 per application hour."
  • Human Capital Costs
    critical 1 source
    industry "Human Capital Costs: Implementing and maintaining an MLOps platform requires specialized talent, including ML platform leads and MLOps engineers."
  • Migration Complexity
    high 1 source
    industry "Migration Complexity: Moving from existing workflows, experiment tracking, and model deployment infrastructure to a new platform like ClearML can involve significant migration effort and may require vendor support."
  • Skill Gaps
    medium 1 source
    industry "Skill Gaps: Teams may face skill gaps in platform-specific concepts (e.g., Kubernetes, infrastructure-as-code, MLOps patterns), which can extend onboarding timelines and increase implementation effort."
  • Integration Delays
    medium 1 source
    industry "Integration Delays: Integrating with legacy data infrastructure, proprietary ML frameworks, or complex multi-cloud environments can cause delays."
  • Opportunity Cost
    critical 1 source
    industry "Opportunity Cost: The cost of not having a mature MLOps practice can manifest in unbudgeted, high-stress events, such as debugging corrupt model states, eroded morale, delayed business impact, and lost revenue due to models degrading silently in p..."
  • Specialized Talent
    high 1 source
    industry "Assigning these tasks to generalist software engineers without MLOps experience can lead to inefficient troubleshooting and suboptimal solutions, increasing operational costs."
  • Data Management and Governance
    medium 1 source
    industry "These costs can escalate with data growth and model complexity."
  • Professional Services
    high 1 source
    industry "Professional Services: For Scale and Enterprise tiers, implementation and professional services fees are not publicly disclosed and should be anticipated."
  • Technical Debt
    critical 1 source
    industry "Technical Debt: The cost of not having a mature MLOps practice can manifest in unbudgeted, high-stress events like debugging corrupt model states, leading to lost engineering hours, eroded morale, and delayed business impact."
  • Operational Costs for Production Models idle AI endpoints can cost between $500 and $23,000 monthly; Model retraining can also cost millions of dollars
    high 1 source
    industry "Model retraining can also cost millions of dollars."
  • On-Premise/VPC Setup
    medium 1 source
    industry "Initial Setup for On-Premise/VPC Deployments: While ClearML offers self-hosting, which can eliminate subscription fees, the initial setup and on-premise configuration can be time-consuming and may involve a learning curve."
Tip

Ask your ClearML 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 2 independent sources
industry G2 B2B reviews
Key claims include inline source attribution. Data verified against multiple independent sources. 13 source citations total.

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