Skip to content
SPECIFICTION
Get listed

ClearML vs Opik

ClearML

clear.ml

Opik

comet.com

Side by side

FigureClearMLOpik
Price from$15/mo$19/mo
Free planYesYes
Free trial—Yes
Open source—Yes
WebYesYes
WindowsYesYes
macOSYesYes
LinuxYesYes
APIYesYes
Self-hostedYesYes
Plans published44
Spec score · MLOps Platforms8.7 (#3)8.9 (#2)
HeadquartersBerkeley, California, USANew York City, United States
IntegrationsThe integrations documentation lists PyTorch, TensorFlow, Keras, scikit-learn, XGBoost, LightGBM, Optuna, Hydra, TensorBoard, Matplotlib, and LangChain among supported integrations.The integration catalog covers TypeScript, Python, Java, .NET and Ruby ecosystems plus no-code tools and OpenTelemetry.
Open sourceClearML says its self-hosted version is 100% open source on GitHub.The core observability and evaluation feature set is available as open-source code that users can download and run locally.
SupportScale includes private Slack channel support and an SLA, while Enterprise includes white-glove support with a custom SLA and professional services.The pricing page lists community and self-service support across plans, email support for Pro and Enterprise, and dedicated support and SLAs for Enterprise.

Plans

ClearML

  • CommunityFree
  • Pro$15 a month
  • EnterprisePriced on request
  • ScalePriced on request

ClearML pricing →

Opik

  • Free CloudFree
  • Open SourceFree
  • Pro Cloud$19 a month
  • EnterprisePriced on request

Opik pricing →

In their own words

ClearML

ClearML is an AI infrastructure platform organized into an Infrastructure Control Plane, AI Development Center, and GenAI App Engine. The Control Plane manages GPU resources across on-premises, cloud, and hybrid environments, including multi-tenant GPU-as-a-Service. The Development Center supports developing, training, testing, and deploying AI/ML models, with monitoring, pipelines, a model repository, and CI/CD integration. The GenAI App Engine deploys LLMs on compute clusters and provides networking, authentication, access control, and monitoring. Experiment tracking, comparisons, artifacts, metrics and plots, and Git version control integration appear across the listed tiers. Integrations include PyTorch, TensorFlow, Keras, scikit-learn, XGBoost, LightGBM, Optuna, Hydra, TensorBoard, Matplotlib, and LangChain; storage integrations include AWS S3, Azure, Google Storage, MinIO, and Backblaze B2. ClearML can be hosted on its servers, self-hosted, or provided as a managed service, with VPC, on-premises including air-gapped, and hybrid options. Community is free; Pro costs $15 a month per user plus usage. Scale and Enterprise pricing is by quote.

Visit clear.ml

Opik

Opik helps teams building applications or agents that call an LLM log actions and evaluate behavior across development, testing, and production. It captures and visualizes traces, supports annotation, and provides audit logs. Its evaluation tools include more than 30 metrics for outcomes such as answer relevance, context precision, task completion, and hallucination. In production, Opik can evaluate traces in real time, alert when criteria fail, and track token use and model costs. Test Suites offer pass/fail assertions, an Agent Playground supports end-to-end tests, and a Prompt Optimizer provides six algorithms. Core observability and evaluation features are available as open-source code for local use. Opik includes a REST API and Python client, with Python and TypeScript SDKs listed, and integrations with more than 40 frameworks, model providers, and gateways. Free Cloud allows up to 10 team members, 25,000 spans per month, and 60-day retention. Pro Cloud costs $19 a month and lists up to 50 team members and 100,000 spans monthly.

Visit comet.com