MLflow Model Registry vs Paperspace Gradient
MLflow Model Registry
mlflow.orgPaperspace Gradient
paperspace.comSide by side
| Figure | MLflow Model Registry | Paperspace Gradient |
|---|---|---|
| Price from | Free | $8/mo |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | Yes |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 17 |
| Spec score · Experiment Tracking | 7.8 (#6) | 8.9 (#2) |
| Purpose | MLflow Model Registry is a centralized model store, API, and UI for managing the lifecycle of machine learning models. | Gradient is a machine learning platform for developing, tracking, and collaborating on machine learning models. |
Plans
Paperspace Gradient
- Free (Individual)Free
- Pro (Individual)$8 a month
- Growth (Individual)$39 a month
- Free (Team)Free
- Pro (Team)$12 a month
- Growth (Team)$39 a month
- T0Free
- T1$12 a month
- FreeFree
- FreeFree
In their own words
MLflow Model Registry
MLflow Model Registry is a model store, API and interface for managing machine-learning models through their lifecycle. It tracks model versions and connects each version to the MLflow run, logged model or notebook that produced it. Teams can organize models with aliases, tags and annotations, register models, add descriptions, and move them between stages such as Staging and Production. On a remote tracking server, MLflow supports basic HTTP authentication and role-based permissions for registered models; basic authentication requires a configured secret key and an admin password of at least 12 characters. When used with Databricks Unity Catalog, the registry supports centralized governance, access controls, cross-workspace access and model lineage. An official Helm chart supports self-hosted Kubernetes deployment. MLflow lists integrations with more than 100 tools, including LangChain, OpenAI and PyTorch, plus support for Python, TypeScript/JavaScript, Java, R and OpenTelemetry. The free Open Source plan uses the Apache 2.0 license. Artifact storage is not supported.
Paperspace Gradient
Paperspace Gradient is a machine learning platform for building, tracking, and collaborating on models. Its browser-based IDE launches GPU-enabled Jupyter notebooks; teams can share projects, invite collaborators, and connect GitHub to manage code and compute resources. Notebook environments run in Docker containers. For deployment, Gradient serves models through API endpoints, with runtime, instance-type, and autoscaling choices. On-demand GPU and IPU instances are available, and paid instance utilization can cost extra beyond plan fees. Gradient supports major machine learning frameworks and libraries. Plans include free options and paid options listed from $8/mo; individual and team plans have different storage allowances, and notebook plans specify limits on notebooks and running sessions. Gradient is offered for beginners, ML/AI engineers, data scientists, researchers, teams, research groups, and startups. Paperspace also lists a Windows, macOS, and Linux beta desktop app, along with centralized permissions and activity logs.