JupyterLab vs Jupyter Notebook
They are two front ends over the same kernels and the same files, so nothing about your code changes. JupyterLab is the IDE-style workspace: tabs, file browser, terminals, side-by-side documents, and the modern extension system. Classic Notebook is the single-document view, and since Notebook 7 it is built on JupyterLab's foundations anyway. Install JupyterLab unless you specifically want the minimal one-notebook-per-tab experience.
At a glance
| JupyterLab | Jupyter Notebook | |
|---|---|---|
| What it is | Project Jupyter's IDE-style interface (tabs, file browser, terminals, extensions) over the same kernels | The open-source notebook standard: a browser interface over a local Python (or R, Julia) kernel |
| AI | Extension-based, principally Jupyter AI; you supply the model keys | None built in; assistance comes from extensions such as Jupyter AI, which you install and key yourself |
| Compute | Same as Jupyter: your machine or your server | Whatever you run it on: your laptop, a lab box, or a server you provision |
| File format | Same .ipynb files as the classic interface | .ipynb JSON with embedded outputs, which is hard to diff, and cells can run out of order |
| Collaboration | Real-time co-editing via the jupyter-collaboration extension; JupyterHub for multi-user deployments | None natively; share files, or run JupyterHub for your team |
| Cost | Free | Free |
| License | Open source (BSD-3-Clause) | Open source (BSD-3-Clause), governed by Project Jupyter |
The core difference
The distinction is interface, not capability. Both talk to the same kernels, open the same .ipynb files, and produce identical results. Anything you can compute in one, you can compute in the other.
JupyterLab is the workspace: multiple notebooks and terminals in one window, a file browser, drag-and-drop cells between notebooks, output panels, and the extension API that new tooling targets. Notebook 7 rebuilt the classic experience on those same foundations, so the modern classic interface is a focused view of JupyterLab rather than a separate codebase.
In practice the reason to prefer the classic view is focus: one notebook, one tab, nothing else on screen, which is what many teaching materials and screenshots assume. The reason to prefer Lab is everything else.
Pick JupyterLab if…
- You want terminals, file browsing, and several notebooks in one window.
- You want the extension ecosystem that current tooling targets.
- You compare notebooks or drag cells between them.
- You are running a shared deployment with JupyterHub.
Pick Jupyter Notebook if…
- You want one notebook per tab and nothing else on screen.
- You are following material written against the classic interface.
- You are teaching beginners and want the smallest possible surface.
Frequently asked questions
- Is JupyterLab replacing Jupyter Notebook?
- Not replacing so much as absorbing. Notebook 7 is built on JupyterLab's components, so the classic experience continues as a simplified view of the same stack rather than as separate software.
- Do I need to convert my notebooks for JupyterLab?
- No. Same .ipynb format, same kernels. The only thing that does not carry over is old classic-Notebook extensions, which target the retired front end and have JupyterLab equivalents.
- Which uses fewer resources?
- The classic interface is marginally lighter in the browser, but the kernel does the real work in both, so on a constrained machine the difference is not what determines whether your notebook runs.
Sources
Every claim about JupyterLab and Jupyter Notebook on this page comes from their own documentation, last checked . Quotas, hardware tiers, and pricing move; check the vendor before relying on a number. Spotted something out of date? Tell us and we will fix it.