Paperspace Gradient vs ZenML

Paperspace Gradient is a machine-learning platform for developing and operating models. It combines managed compute with experiment tracking, a model registry, pipeline orchestration, model serving and data versioning. Gradient is available on Linux, macOS, Windows and the web. Free plans for individual users and teams include 5 GB of storage; no hourly or maximum monthly price is shown for those plans. Paid plans are billed hourly up to a maximum monthly price. Pro — User costs $8 a month and includes 15 GB of storage, while Growth — User costs $39 a month with 50 GB. Team plans include Pro — Team at $12 a month with 15 GB of storage and Growth — Team at $39 a month with 50 GB. Those listed paid prices are maximum monthly prices, not a statement of a fixed hourly charge. The combination of compute and tools for tracking data, organizing pipelines and serving models covers several stages of machine-learning work.

ZenML orchestrates AI and machine-learning pipelines and agents written in Python. Pipelines can run on Kubernetes, Vertex AI, SageMaker, AzureML, or a laptop without rewriting code. ZenML versions step outputs such as models and evaluation datasets, supports re-execution from any step, and reuses cached results when code and inputs have not changed. Deployment choices include local, SaaS, and self-hosted setups, with Docker and Kubernetes Helm methods. ZenML says it stores metadata while data, artifacts, and compute remain in the customer's infrastructure or VPC. Its integrations directory lists 66 tools, including LangGraph, OpenAI Agents SDK, PyTorch, MLflow, AWS, and Google Cloud Vertex AI Pipelines. The self-hosted Open Source plan is free and includes unlimited executions and projects. Scale costs $999 a month and includes 2,000 executions, three projects, and five snapshots. Enterprise has custom pricing and adds SSO, custom-role RBAC, audit logs, and air-gapped deployment. ZenML says it is SOC 2 Type II and ISO 27001 certified.