Paperspace Notebooks review
A flexible hosted notebook workspace with free access and paid capacity tiers.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Paperspace Notebooks is a managed, browser-based Jupyter IDE for data exploration, machine-learning development, and model building. It supports Python and Jupyter files, with CPU, GPU, and multi-GPU machine selection. Users can start from pre-built templates or custom Docker-based runtimes, attach persistent storage, and share notebooks with collaborators. The service is suited to individuals, teams, and developers who want hosted notebook infrastructure rather than a local environment.
The plan structure covers both individual use and larger notebook deployments. Free provides public projects, 5GB of storage, and basic instances. Pro costs $8 per month and adds private projects, 15GB of storage, mid-range instances, and faster free GPUs. Growth costs $39 per month and adds 50GB of storage, high-end instances, and expert support. Separate T0, T1, and T2 plans focus on notebook capacity: T0 includes public notebooks, 10GB of persistent storage, 10 total notebooks, and one running notebook; T1 costs $12 per user per month and adds private notebooks, 500GB of persistent storage, 100 total notebooks, and 10 running notebooks; T2 includes private notebooks, scalable storage, and unlimited notebooks and running notebooks. Compute usage can incur separate hourly charges in addition to subscription prices.
Paperspace’s strongest fit is a workflow that needs more than a basic notebook editor. Persistent shared storage, public links, project forking, collaborators, teams, permissions, dataset tracking, versioned datasets, terminals, system metrics, log streaming, and machine auto-shutdown controls support a broader development process. Python CLI, SDK, and API management add programmatic control, while the web and API platforms support browser-based and automated workflows. Choose it for hosted GPU-backed notebooks, containerized environments, and flexible collaboration. It is less suitable when private work must fit within the free plan or when predictable costs are required without separate compute charges.
Paperspace Notebooks pros and cons
- Where it wins
- CPU, GPU, and multi-GPU machine selection
- Custom Docker runtimes, templates, and persistent shared storage
- Notebook sharing, permissions, datasets, APIs, CLI, and SDK support
- Where it doesn't
- Free projects are public and include only 5GB of storage
- Compute usage can add separate hourly charges
- Some advanced capacity requires paid plans
Paperspace Notebooks fact sheet, pricing and score →
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