LabML vs ZenML
LabML
labml.ai
ZenML
zenml.ioSide by side
| Figure | LabML | ZenML |
|---|---|---|
| Price from | — | $999/mo |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| iOS | Yes | — |
| Android | Yes | — |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 0 | 3 |
| Spec score · ML Experiment Tracking Software | 7.7 (#12) | 7.8 (#11) |
| Purpose | LabML is an open-source platform for monitoring deep learning experiments and hardware usage. | ZenML orchestrates AI and machine-learning pipelines and agents written in Python. |
| Support | The LabML app page lists contact email [email protected]. | The Open Source plan includes community support, Scale includes priority support, and Enterprise includes dedicated support with an SLA. |
Plans
In their own words
ZenML
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.