Paperspace: Cloud GPU and Machine Learning Platform
Paperspace helps data science teams and software companies access high-performance compute. It is designed for businesses that need scalable GPU resources for AI training and 3D rendering.
At a glance
- Best for
- Software Companies, Data Science Teams, ML Engineers, AI Researchers
- Pricing
- Pricing includes a free tier and paid platform plans starting at $8 per month. GPU compute is billed hourly, ranging from $0.45 to $3.09 per hour depending on the instance.
- Key use cases
- AI Model Development, 3D Rendering and Simulation, Production Model Deployment, Enterprise Virtual Desktops
- Official website
- Visit paperspace official website
Paperspace is a cloud computing platform specialized in GPU acceleration, now part of DigitalOcean. It provides infrastructure options ranging from managed notebooks for prototyping to dedicated GPU instances for large-scale workloads.
The platform is designed for ML engineers, data scientists, and researchers who require access to hardware such as NVIDIA H100 and A100 GPUs. It supports the machine learning lifecycle, including development, training, and deployment as API endpoints.
Beyond AI, the platform supports high-performance tasks such as 3D graphics, simulations, and virtual desktop infrastructure (VDI).
Buyers should note that Paperspace is transitioning toward a unified product suite under DigitalOcean, and new users are encouraged to evaluate DigitalOcean's broader AI offerings.
Key Features
Gradient ML Platform
A managed environment used to develop, track, and collaborate on machine learning models.
NVIDIA GPU Fleet
On-demand access to various GPUs, including H100, A100, and V100, for accelerated compute.
Managed Notebooks
Hosted notebooks for data exploration and building initial proofs of concept.
Deployments Service
Capability to convert trained AI models into scalable API endpoints.
Core GPU Cloud
Managed virtual servers and desktops with a variety of compute and storage options.
Workflows (Beta)
A tool designed to help automate machine learning tasks.
Use Cases
AI Model Development
Developing and fine-tuning machine learning models using cloud GPUs.
3D Rendering and Simulation
Using high-performance workstations and render nodes for 3D graphics and complex simulations.
Production Model Deployment
Deploying trained models as API endpoints to support applications.
Enterprise Virtual Desktops
Implementing virtual desktop infrastructure (VDI) with centralized management for teams.
Best For
- Software Companies
- Data Science Teams
- ML Engineers
- AI Researchers
Pricing
Pricing includes a free tier and paid platform plans starting at $8 per month. GPU compute is billed hourly, ranging from $0.45 to $3.09 per hour depending on the instance.
FAQ
How does Paperspace pricing work?
- Users pay for a platform plan (starting at $0) and are then charged hourly for compute usage and $0.29/GB for storage overages.
What GPUs are available on the platform?
- Paperspace offers a range of NVIDIA GPUs, including the H100, A100, V100, A6000, and others.
Is Paperspace still a standalone company?
- No, Paperspace is now part of DigitalOcean. While existing services are available, new users are recommended to explore DigitalOcean's AI product lineup.
Source category: Software Development
Source subcategory: Machine Learning Platform
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Categories
Software Type
How AI is used
Paperspace is a cloud GPU platform for developers and data science teams to build and deploy AI/ML models. It supports workflows from notebook prototyping to production deployment using NVIDIA GPUs. The platform is now integrated into DigitalOcean.
Pros & Cons
Pros
- Wide variety of NVIDIA GPU options
- Hourly on-demand pricing
- Includes a free tier for beginners
- Supports Linux and Windows licenses for desktops
Cons
- New users are encouraged to use DigitalOcean as the platform transitions
- Free tier has a 12-hour auto-shutdown limit
- Storage overages are billed separately at $0.29/GB
