ML Workspace vs Paperspace Gradient
ML Workspace
mltooling.orgPaperspace Gradient
paperspace.comSide by side
| Figure | ML Workspace | Paperspace Gradient |
|---|---|---|
| Price from | Free | $8/mo |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | Yes |
| Web | Yes | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | — | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 17 |
| Spec score · Data Science Platforms | 8.3 (#7) | 8.7 (#3) |
| Purpose | ML Workspace is an all-in-one web-based IDE specialized for machine learning and data science. | Gradient is a machine learning platform for developing, tracking, and collaborating on machine learning models. |
| Security | The documentation describes token or basic authentication options and configurable SSL/HTTPS support. | Paperspace describes centralized permissions and activity logs, and says its security team monitors threats around the clock. |
| Support | The maintainers say they cannot provide individual support by email and direct users to public support channels; the page lists [email protected] for other requests. | Paperspace lists free ticket-based support seven days a week and contract-based enterprise support with infrastructure assistance and customer success managers. |
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
ML Workspace
ML Workspace is a self-deployed, web-based development environment for machine learning and data science. It brings browser-accessible Jupyter, JupyterLab, Visual Studio Code, and a Linux desktop GUI together, with libraries such as TensorFlow, PyTorch, Keras, and scikit-learn in its main image. Git-related tools include Ungit, Jupytext, nbdime, and a Jupyter extension for pushing notebooks. TensorBoard supports training monitoring, while Netdata and Glances cover hardware monitoring. The workspace can provide a remote runtime for Jupyter, VS Code, PyCharm, Colab, and Atom Hydrogen, typically through passwordless SSH, and can be accessed through a browser, SSH, or VNC. Image options include minimal, R, Spark, and GPU variants; the GPU flavor requires compatible Nvidia drivers and supports CUDA 11.2. Docker is required, with images deployable on Mac, Linux, and Windows. The project describes token or basic authentication and configurable SSL/HTTPS. It is designed for one user, and at least 2 CPUs and 500 MB of memory are recommended for stable use. The free plan costs nothing.
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.