ClearML pricing 2026: plans and costs
How AI answers describe ClearML pricing
If transparent, publicly listed pricing is your priority, I would shortlist LUML, ClearML, and Comet.
Compared to: MLflow · Weights & Biases · Amazon SageMaker AI
- ClearML – request annual pricing for hosted, VPC, or on-prem deployments.
- ClearML — listed at $15/month monthly versus $180/year annually, representing about $420/year in savings compared with the cited monthly pricing.
Quick pricing summary
- Community: $0 month
- Pro: $15 user/month + usage
- Scale: Custom (custom quote)
- Enterprise: Custom (custom quote)
- Worth noting: Self-hosted open source version also available free on GitHub. Pro billed per user plus pay-as-you-go usage.
Plans
Community
$0 month
- For teams up to 3
- Dataset Versioning
- Model Training
- Experiment Management
- Model Repository
- Artifacts
- Pipelines
- Agent Orchestration
- CI/CD Automation
- Reports
- 100GB Free Artifact Storage
- 1GB Metric Events
- 1M API Calls/Month
Pro
$15 user/month + usage
- For teams up to 10
- Cloud Auto Scaling (AWS, GCP, Azure)
- Hyperparameter Optimization
- Pipeline Triggers and Automations
- Dashboards
- Unlimited, Pay-As-You-go Usage (Storage and Activity)
- 120GB Free Artifact Storage
- 1.2GB Metric Events
- 1.2M API Calls/Month
Scale
Custom custom quote
- For organizations with 8-48 GPUs
- VPC only
- Hyper-Datasets
- Fine-tuning
- IDE Launcher
- Vector Database integration
- Kubernetes Integration
- Task Scheduling and Triggering
- Alerts
- SSO integration
- Private Slack Channel Support
- SLA
- Hardware- and Cloud-agnostic Orchestration
- Multi-cluster Support
- Fractional GPUs
Enterprise
Custom custom quote
- For VPC or On-prem Cluster
- ClearML Custom Apps
- Configuration Vault
- Slurm/PBS integration
- LDAP Integration
- Role-based Access Control
- White-glove Support with Custom SLA
- Professional Services
- Advanced Scheduling and Quota Management
- Dynamic Fractional GPUs
- Resource Allocation Policy Management
- On-premise, Air-gapped, Multi-cloud, or Hybrid setups
What you get on each plan
| Feature | Community | Pro | Scale | Enterprise |
|---|---|---|---|---|
| Max team size | 3 | 10 | 8-48 GPUs | Multiple large projects |
| Cloud Auto Scaling | — | ✓ | ✓ | ✓ |
| Hyperparameter Optimization (UI) | — | ✓ | ✓ | ✓ |
| Hyper-Datasets | — | — | ✓ | ✓ |
| Kubernetes Integration | — | — | ✓ | ✓ |
| Single Sign On | — | — | ✓ | ✓ |
| Role-based Access Control | — | — | — | ✓ |
| LDAP Integration | — | — | — | ✓ |
| Multi-cluster Support | — | — | — | ✓ |
| Dynamic Fractional GPU | — | — | — | ✓ |
| Support | — | — | Dedicated Slack Channel, Standard SLA | White Glove, Custom SLA |
| Deployment | SaaS | SaaS | VPC - Single Server | VPC / On-prem cluster |
Hidden costs & add-ons
| Cost driver | Price | When it applies |
|---|---|---|
| Additional Artifact Storage | $0.1 / 1GB | Pro |
| Additional Metric Events | $0.01 / 1MB | Pro |
| Additional API Calls | $1 / 100K | Pro |
| Application usage | $0.04/hr per Application | Pro |
ClearML pricing vs alternatives
| Brand | Entry price | Free plan | Model | Best for | |
|---|---|---|---|---|---|
| ClearML | Free; paid from $15 per seat / mo | Yes | Per seat | — | |
| MLflow | — | — | — | Teams of all sizes building LLM applications, agents and ML models who want open source tooling without vendor lock-in. | Compare → |
| Weights & Biases | — | — | — | — | Compare → |
| Amazon SageMaker AI | — | — | — | — | Compare → |
| AWS | — | — | — | — | Compare → |
List prices as published on clear.ml/pricing. Totals are worked examples, not quotes.