Blazing Fast GPU cloud built for Machine Learning
Save 80% on GPU Instances with transparent and lowest pricing.
Meet Paperspace
From research to production
Start something new or scale up an existing project on affordable cloud GPUs. Replace high upfront costs of managing servers with predictable hourly pricing.
affordable GPU compute
Low-cost GPUs with per-second billing
Save up to 70% on compute costs
Spend significantly less on your GPU compute compared to the major public clouds or buying your own servers.
Predictable costs
Scale when you need, stop paying when you don't. On-demand pricing means you only pay for what you use.
No commitments
Easily change instance types anytime so you always have access to the mix of cost and performance. Cancel anytime.
Go from signup to training a model in seconds
Preloaded with ML frameworks
Choose "ML in a Box" template that comes preinstalled with all the major ML frameworks and CUDA® drivers.
Latest NVIDIA GPUs
Choose from the largest GPU catalog in the world. Leverage the latest NVIDIA GPUs including Ampere A100s with up to 8 GPUs.
Root access, connect with SSH
Bring your SSH key and connect directly to your VM with full root access.
Limitless computing power on demand
Simple management interface & API
Easily launch a large cluster of compute nodes, zero DevOps required. Track realtime utilization across your team. Full API access.
Lightning fast networking
Each instance is connected to a 10 Gbps backend network with 1Gbps internet connectivity.
The latest state-of-the-art infrastructure
With one of the largest catalog of GPUs in the world, you always have access to the best hardware available.
Exploring different cloud GPU options?
Check out The Ultimate Guide to Cloud GPU Providers!
- 10+ GPU cloud providers analyzed (including AWS EC2, Azure, and more)
- 50+ GPU instances analyzed
- Comprehensive comparisons across price, performance, and more
You're in good company. Join over 500,000 users on Paperspace.
500K+ Users
100M+ Compute hours
1M+ Jupyter notebooks
What others are saying
"For ML applications, I’ve found @HelloPaperspace to have the best UI / UX by far"
Lewis Tunstall (LLM Engineering & Research)
"I'm very impressed with @HelloPaperspace GPU cloud and an ability to create templates. One API call and 5 minutes later I'm training physics-informed neural networks through http://SIML.ai's environment ( @nvidia Modulus + JupyterLab + VS Code + Tensorboard + netdata)."
@michaeltakac (ML Engineer)
"Have been using @HelloPaperspace Gradient Notebooks and it has been an amazing experience so far. ... A true local-like development environment feel 😄"
Anubhav Singh (Developer)
"I just checked out @HelloPaperspace and wow its soooo beautiful"
Sumanth Neerumalla (Full stack SWE)
"I came across a very exciting feature on Paperspace: they mounted additional storage to every machine for free. That storage has public machine learning datasets. OMG, this is so cool. Great job @HelloPaperspace!!! 👏"
Alisher Abdulkhaev (Head of Vision AI)
"Trying out @HelloPaperspace after all the problems with colab so far the transparency about what you're getting for your money (and what instances are available) is nice. But all the system information graphs are my favorite."
@duskvirkus (ML Intern)
"Just tried Gradient from @HelloPaperspace. Man that thing is super easy to use. #MachineLearning #CloudComputing"
Milos Svana (AI/ML Engineer and Researcher)
"First time using @HelloPaperspace. Great way to spend more time learning and practicing ML rather than debugging / setting up a Cloud instance."
James Teow (Software Engineer)
"We're testing deployment to @HelloPaperspace GPU cloud. So far it works great! Next week we'll add possibility to launch http://SIML.ai instance on it through Model Engineer - one click and you'll be up-and-running!"
@siml_ai (Simulation Software by DimensionLab)