PaperSpace: The Cloud GPUs for AI and Creative Work

Cloud computing has transformed the way people access powerful hardware. Instead of buying expensive machines, users can now rent computing resources through the internet on demand. One platform that has become well-known in the creative and AI community is Paperspace. Acquired by DigitalOcean in 2023, Paperspace provides GPU-powered cloud instances that make it possible to run everything from deep learning to 3D rendering and AI image generation.

In this article, we’ll take a deep dive into what Paperspace is, how it works, the GPUs it offers, why it’s popular for AI art tools like Stable Diffusion, and whether it’s the right choice for you.

What Is Paperspace?

Paperspace is a cloud computing platform designed to give users access to virtual machines (VMs) and high-performance GPUs (graphics processing units). GPUs are critical for modern AI applications because they can perform massive parallel computations much faster than CPUs.

Whereas traditional cloud services like AWS or Google Cloud can be complex and overwhelming, Paperspace has carved out a niche by being simpler, cost-effective, and creator-friendly. It bridges the gap between professional AI developers and everyday creators by offering GPU access in an environment that’s easy to set up.

With Paperspace, you can:

• Train deep learning models

• Run AI frameworks like PyTorch or TensorFlow

• Generate images with Stable Diffusion

• Perform 3D rendering and visualization

• Power up creative workflows without buying a high-end workstation

How Paperspace Works

At its core, Paperspace works like any other cloud service:

1. Sign up for an account
   Users create a Paperspace account to access their dashboard.

2. Choose a machine type
   Paperspace lets you pick from different “machines” that are pre-configured with hardware resources. These include CPU-only options and GPU-powered instances.

3. Launch a workspace or notebook

   • Gradient: A Paperspace service tailored for machine learning. It provides Jupyter notebooks preloaded with popular AI frameworks.

   • Core: Traditional virtual machines with GPU power.

4. Install software or use prebuilt templates
   For AI art, many users run Stable Diffusion templates available directly inside Paperspace notebooks.

5. Pay as you go
   You only pay for the GPU time you use, making it flexible for individuals and businesses.

Paperspace GPU Options

One of the strengths of Paperspace is its variety of GPUs. Depending on your budget and needs, you can rent machines that are powerful enough for basic tasks or cutting-edge GPUs for demanding AI workloads.

Some of the most common GPUs available include:

• NVIDIA T4 – Affordable, good for light AI tasks and beginners.

• NVIDIA RTX4000/A4000 – Mid-range GPU, decent for AI image generation.

• NVIDIA A100 – One of the most powerful GPUs for large-scale deep learning.

• NVIDIA A6000 – High-end workstation GPU with large VRAM, great for rendering and complex AI workflows.

This flexibility means you can start small, test workflows, and scale up to professional-grade hardware when needed.

Why Creators Use Paperspace for AI Image Generation

While Paperspace is a general-purpose cloud platform, it has become popular in the AI art community, especially for running Stable Diffusion. Stable Diffusion is a text-to-image AI model that requires a GPU with decent VRAM. Running it on a personal laptop can be difficult, but with Paperspace, you can access GPUs strong enough to generate high-resolution, detailed images.

Key reasons artists choose Paperspace for Stable Diffusion:

• No need for expensive hardware: A $2,000 GPU workstation isn’t required—you can rent the equivalent power by the hour.

• Pre-configured environments: Paperspace offers ready-to-go notebooks for Stable Diffusion. You don’t need to spend hours troubleshooting installations.

• Scalability: Want to generate 100 images quickly? Just rent a stronger GPU temporarily.

• Accessibility: Works directly in the browser, no downloads necessary.

Gradient vs. Core: Choosing the Right Environment

Paperspace offers two main environments, and understanding them is key to choosing the right one:

1. Gradient

   • Cloud-based Jupyter notebooks.

   • Ideal for machine learning and AI image generation.

   • Preloaded with frameworks like PyTorch and TensorFlow.

   • Great for beginners who want simplicity.

2. Core

   • Full virtual machines with a customizable OS.

   • Ideal if you want more control, run 3D software, or experiment beyond notebooks.

   • Great for developers and advanced users.

For most AI art creators, Gradient notebooks are the fastest way to get started.

Pricing Overview

Pricing is where Paperspace shines compared to bigger cloud providers. While AWS and Google Cloud can feel intimidating with their complex pricing models, Paperspace uses a straightforward pay-per-hour or monthly subscription system.

Example Pricing:

• NVIDIA T4: ~$0.45/hour

• NVIDIA RTX4000: ~$0.60–0.70/hour

• NVIDIA A100: ~$2.30/hour

• NVIDIA A6000: ~$2.50–$3.00/hour

They also offer storage fees (for keeping your work saved) and monthly billing options for people who prefer predictable costs. For artists, this often works out cheaper than building a local PC with a powerful GPU. For example, renting an A100 for a few hours a week is far more affordable than buying one outright for thousands of dollars.

Pros of Paperspace

1. Ease of use – User-friendly interface, less technical than AWS or Google Cloud.

2. GPU variety – Access everything from budget GPUs to high-end A100s.

3. Prebuilt notebooks – Especially for Stable Diffusion and machine learning.

4. Affordable entry point – Pay only for what you use.

5. Flexible – Good for AI, rendering, 3D, and general computing.

Cons of Paperspace

1. Wait times for premium GPUs – Popular GPUs like A100s may not always be available instantly.

2. Storage costs – You’ll pay extra if you want to save large datasets or many projects.

3. Not as beginner-focused as some competitors – While simpler than AWS, it can still feel technical for first-time users.

Use Cases Beyond AI Art

While Stable Diffusion and AI art generation have brought many creators to Paperspace, the platform supports a wide range of use cases:

• Deep learning research – Train large models without investing in local GPUs.

• 3D rendering – Use GPU power for Blender, Maya, and other rendering tasks.

• Game development – Test and build GPU-heavy games in virtual environments.

• Business applications – Companies can run simulations, analytics, and GPU-powered software.

Paperspace vs. Other Cloud GPU Platforms

If you’re deciding between Paperspace and alternatives, here’s a quick comparison:

• ThinkDiffusion / RunDiffusion – More beginner-friendly for Stable Diffusion only.

• RunPod – Similar to Paperspace but often cheaper, with strong community templates.

• Vast.ai – Cheapest, but more DIY and less polished.

• Google Colab Pro – Cheapest subscription, but session timeouts limit reliability.

Paperspace sits in the middle: more professional and flexible than hobbyist services, but more user-friendly than enterprise-level clouds.

Who Should Use Paperspace?

Paperspace is best suited for:

• AI artists who want to run Stable Diffusion at higher speeds and resolutions.

• Students and researchers learning machine learning without expensive hardware.

• Freelancers and studios that need GPU rendering for creative projects.

• Developers building AI-powered apps.

If you’re just casually experimenting, Google Colab might be cheaper. But if you want reliable GPU access with flexibility, Paperspace is an excellent choice.

Final Thoughts

Paperspace has built a reputation as a creator-friendly cloud platform that makes GPU power accessible to anyone. By balancing simplicity with flexibility, it has become a go-to choice for artists, researchers, and developers alike.

For those exploring AI image generation, Paperspace is particularly appealing. Its prebuilt notebooks and GPU variety make running Stable Diffusion straightforward, without the headaches of setup or expensive local hardware.

As AI tools become more demanding, the need for GPU access will only grow. Paperspace provides a way to stay at the cutting edge—without breaking the bank.