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Google Colab vs ML Workspace

Google Colab

colab.research.google.com

ML Workspace

mltooling.org

Side by side

FigureGoogle ColabML Workspace
Price from$8.33/moFree
Free planYesYes
Free trial——
Open source——
WebYesYes
Windows—Yes
macOS—Yes
Linux—Yes
APIYes—
Self-hostedYesYes
Plans published91
Spec score · Data Science Platforms9.0 (#2)8.3 (#7)
IntegrationsUsers can import data from Google Drive, spreadsheets, GitHub, and other sources, and the site lists Google Cloud Storage, Sheets, and BigQuery resources.Listed tools and integrations include Git, TensorBoard, Netdata, Jupyter, JupyterLab, and Visual Studio Code.
SupportUsers can report bugs or ask questions through Help > Send feedback in any Colab notebook.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.

Plans

Google Colab

  • Colab Pro$8.33 a month
  • Colab Pro+$41.66 a month
  • ColabFree
  • Colab freeFree
  • Colab EnterprisePriced on request
  • Colab ProPrice not published
  • Colab Pro+Price not published
  • Colab Pro / Pro+ / Pay As You GoPriced on request
  • Pay As You GoPrice not published

Google Colab pricing →

ML Workspace

  • ML WorkspaceFree

ML Workspace pricing →

In their own words

Google Colab

Google Colab lets users write and run Python in a browser without configuring a local environment, with access to GPUs and notebook sharing. Its hosted Jupyter notebooks combine executable code with rich text, images, HTML, and LaTeX. Data can come from Google Drive, spreadsheets, GitHub, and other sources, with Google Cloud Storage, Sheets, and BigQuery resources listed for integration. Colab AI can generate or transform code, explain Python libraries, suggest fixes, and perform multi-step data-analysis workflows. By default, it does not access Drive files or user secrets, though it can generate code to access them when explicitly requested. Google says generative-AI features collect prompts, related code, outputs, usage information, and feedback; human reviewers may process that data for up to 18 months. Free notebooks can run for at most 12 hours, depending on availability and usage. Pro+ supports continuous execution up to 24 hours when enough compute units are available. Colab also has a Visual Studio Code extension and a beta, allowlist-gated API. Paid plans start at 8.33 USD/user/mo (annual).

Visit colab.research.google.com

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.

Visit mltooling.org