Paperspace

Build, train, and deploy AI/ML models on accelerated cloud GPUs with simplicity and scalability.

Hosting & Deployment AI Model Deployment

4.0(36 across the web)

What is Paperspace?

Paperspace (hosting & deployment): Build, train, and deploy AI/ML models on accelerated cloud GPUs with simplicity and scalability. Paperspace, now part of DigitalOcean, provides an accelerated cloud computing platform specifically designed for AI and Machine Learning workloads. It offers access to powerful GPUs, including NVIDIA H100, enabling users to develop, train, and deploy AI applications efficiently. Key capabilities: NVIDIA H100 GPU access for AI/ML workloads, ML platform for building, training, and deploying models (Gradient), Fully-managed cloud GPU platform (CORE), 1-click hosted Jupyter Notebooks, End-to-end MLOps capabilities. Paperspace ships a free plan plus paid tiers that unlock as usage grows. Buyers most often compare Paperspace against Baseten, Replicate, Groq.

TL;DR - Paperspace

Accelerated cloud GPU platform for AI/ML development.
Supports full ML lifecycle: develop, train, and deploy models.
Offers scalable, on-demand GPU access with per-second billing.

Pricing: Free plan available

Best for: Growing teams

4.0/5 across review platforms

Pros & Cons

Pros

Significantly reduces compute costs compared to major public clouds or self-hosting.
Simplifies AI/ML infrastructure management, allowing focus on model development.
Offers flexible, on-demand scaling with no long-term commitments.
Provides a comprehensive platform for the entire ML lifecycle, from development to deployment.
Includes collaboration features for team-based projects.

Cons

Specific instance types and their availability may vary.
Free tier has limitations on storage and auto-shutdown duration.

Ratings Across the Web

4(36 reviews)

Ratings aggregated from independent review platforms. Learn more

Key Features

NVIDIA H100 GPU access for AI/ML workloadsML platform for building, training, and deploying models (Gradient)Fully-managed cloud GPU platform (CORE)1-click hosted Jupyter NotebooksEnd-to-end MLOps capabilitiesLow-cost GPUs with per-second billingOn-demand pricing with no commitmentsInstant provisioning of instances

Pricing Plans

Free

FREE GPU
Public projects
Auto-shutdown (12 hour limit)
5GB storage
Basic instances

Pro

$8 per month

Private projects
15GB storage
Auto-shutdown (configurable)
Mid-range instances
Faster free GPUs (based on availability)

Growth

$39 per month

Private projects
50GB storage
Auto-shutdown (configurable)
High-end instances
Expert Support

T0 Small Teams

$0 + utilization costs on paid instance types

Low Instance Types
Public Notebooks
10GB Persistent Storage included
Auto-shutdown (12 hour limit)
Total Notebooks: 10
Running Notebook limit: 1

T1 Mid-Size Teams

$12 user/month

Low - Mid Instance Types
Private Notebooks
500GB Persistent Storage included
Auto-shutdown (configurable)
Total Notebooks: 100
Running Notebook limit: 10

T2 Large Teams

Contact Sales

Low - High Instance Types
Private Notebooks
Scalable Storage
Auto-shutdown (configurable)
Unlimited Notebooks
Unlimited Running Notebooks

Enterprise

Contact Sales

Host Gradient on your own infrastructure
Run without limits
Custom plans

View full pricing

About Paperspace

LCLouis CorneloupUpdated May 11, 2026

Paperspace, now part of DigitalOcean, provides an accelerated cloud computing platform specifically designed for AI and Machine Learning workloads. It offers access to powerful GPUs, including NVIDIA H100, enabling users to develop, train, and deploy AI applications efficiently. The platform is built to simplify complex infrastructure management, allowing individuals and teams to focus on model development rather than server maintenance. It supports the entire ML lifecycle from launching notebooks for proof-of-concept to training and fine-tuning models, and finally converting them into scalable API endpoints. The platform caters to a wide range of users, from individual ML engineers and data scientists to large teams and startups. It emphasizes speed, affordability, and scalability, offering low-cost GPUs with per-second billing and no long-term commitments. Paperspace aims to remove infrastructure bottlenecks, providing features like instant provisioning, job scheduling, resource provisioning, and automatic versioning. It also includes collaboration tools and insights for team management, making it a comprehensive solution for building and scaling next-generation AI applications.

How we evaluate tools →Source: paperspace.com

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Paperspace FAQ

How does Paperspace's per-second billing for GPUs compare to other cloud providers?

Paperspace offers per-second billing for GPU compute, which can result in up to 70% savings compared to major public clouds. This model ensures you only pay for the exact duration of your usage, eliminating costs for idle time.

What is the difference between the CORE and Gradient products within Paperspace?

CORE is a fully-managed cloud GPU platform providing virtual servers, storage, and networking options for general accelerated computing. Gradient is specifically an ML platform built on CORE, designed for building, training, and deploying Machine Learning models of any size and complexity, offering features like 1-click hosted Notebooks and MLOps tools.

Can I integrate Paperspace with my existing private cloud or on-premise infrastructure?

Yes, Paperspace offers solutions for private cloud, on-premise deployments, and hybrid environments. The Managed Service and Private Cluster options for Gradient allow for deployment on private Azure/AWS/GCP/Paperspace clouds or on-premise installations like DGX.

What kind of reproducibility features does Paperspace offer for ML experiments?

Paperspace provides full reproducibility for ML experiments through automatic versioning, tagging, and life-cycle management. This ensures that your models and their development history are tracked and can be recreated consistently.

How does the auto-shutdown feature work for Notebooks, and can it be configured?

Notebooks on Paperspace include an auto-shutdown feature to manage costs. For the Free plan, there's a 12-hour limit. For Pro and Growth plans, the auto-shutdown is configurable, allowing users to set their preferred duration before instances are automatically shut down.

What types of GPUs are available on the Paperspace platform for AI/ML workloads?

Paperspace provides access to a range of powerful GPUs, including NVIDIA H100, which are optimized for AI and ML workloads. The platform offers various instance types, from basic to high-end, to suit different computational needs.

Source: paperspace.com