ClearML vs Oxen

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.

Oxen combines access to AI models with tools for organizing and versioning the data used with them. Its unified API provides more than 200 text, image, video, and audio models. Oxen versions prompts, media, labels, metadata, generated outputs, and training examples, and says it can scale to millions of files and terabytes of data. Teams can browse datasets, review generated work, experiment across branches, and track who changed what and when. Users can fine-tune supported open-source models on proprietary text, image, and video datasets. Data can be read or written through the Python API, HTTP API, command line, or open-source server. Private deployment is available in a customer’s VPC or fully on-premises. Explorer is free and includes unlimited public repositories and collaborators, five private repositories, up to three private collaborators, and 50gb each of storage and transfer. Hacker costs $30 a month; Pro costs $60 a month. Model inference is pay as you go; dedicated GPUs are charged per second and shut down after 15 minutes of inactivity.