Paperspace is still running, but it isn't the same choice for every new user that it once was. If you need a managed Windows workstation for creative software, Vagon Cloud Computer is the closest fit in this guide. If you need Linux GPU compute for AI, look at Runpod or DigitalOcean GPU Droplets. For company-managed VDI, Amazon WorkSpaces or Azure Virtual Desktop makes more sense. Parsec, Shadow, and GeForce NOW solve different parts of the problem.

That distinction matters because a cloud workstation, a GPU server, remote access software, and a cloud gaming service aren't interchangeable. This guide is for people replacing or evaluating a Paperspace workflow, not a directory of every GPU provider.

Which Paperspace alternative fits your workload?

Start with the job you need the service to do. A video editor who needs Windows, Adobe apps, persistent files, and smooth desktop streaming has different requirements from a developer training a model in a Linux container.

Here is the short version:

Pricing and availability were checked on August 26, 2026. Providers can change prices, regional inventory, trials, and plan terms. Check the relevant checkout page for your location before buying.

For most artists, designers, architects, video editors, and game developers looking for a straightforward Paperspace alternative, the first question is whether Windows is required. If it is, a managed cloud computer such as Vagon will usually be a more direct fit than assembling a GPU VM, storage, licensing, security, and remote streaming yourself.

What actually changed when Paperspace became part of DigitalOcean?

DigitalOcean acquired Paperspace on July 6, 2023. Paperspace initially said it would remain a standalone business unit in the near term and that customers would see no immediate service changes. Since then, the brands and product portfolios have moved closer together, but that doesn't mean Paperspace closed or that every account was moved into one new system.

DigitalOcean's current transition page says existing Paperspace users can still access legacy products through the Paperspace Cloud Console. It also says core Paperspace products remain available, while recommending that new AI customers look at DigitalOcean's newer GPU and AI services.

Core and Gradient are still documented. Paperspace currently lists Machines, Notebooks, Workflows, and Deployments. Accounts, billing, support, and the Paperspace console also remain visible as separate parts of the product experience. Even DigitalOcean's standard support plans don't automatically apply to Paperspace.

The biggest practical change for creative users came on July 1, 2024. Paperspace retired Windows-based templates for new accounts. People who joined before that date can still start, create, and manage Windows template machines, but newer users cannot. Paperspace also retired its older NVIDIA GRID machine types.

That account-age rule explains conflicting advice on Reddit and in older tutorials. One user may still see Windows while another does not. Community threads reveal the confusion, but official documentation settles the product fact.

Developers should also know that Paperspace retired its legacy Core and Gradient API endpoints in May 2024 in favor of a newer API. Existing scripts built on older endpoints may therefore need work even when the underlying product is still available.

So “DigitalOcean migration” is useful shorthand for the change readers are noticing, but acquisition and ongoing product unification are more precise. The reason to consider an alternative isn't that Paperspace disappeared. It is that the current product, OS availability, regional footprint, and future direction may no longer match the original workflow.

Which options work for creative Windows workstations and team VDI?

Creative applications need more than a GPU model on a pricing page. The service also has to deliver a usable Windows desktop, persistent project files, acceptable visual quality, low interactive latency, application licensing that permits cloud use, and a region close enough to the user.

Vagon Cloud Computer: the direct fit for individual creative work

Vagon Cloud Computer packages the computer and remote experience together. You create a persistent Windows desktop, access it through a browser, choose a CPU or NVIDIA GPU performance level, and change performance while keeping the same computer and files. Its application catalog can also preinstall common software during setup.

That arrangement fits workflows such as Blender, Unreal Engine, 3D design, CAD, architecture, video editing, and other Windows-based professional work. It removes much of the infrastructure work involved in turning a generic cloud GPU into an interactive workstation.

At the time of checking, Vagon publicly listed examples including Planet with a 16 GB NVIDIA T4 GPU at $0.99 per active hour and Spark with a 24 GB GPU at $1.67 per active hour. Those rates aren't the whole bill. The applicable storage or plan component also matters, so compare the exact configuration in checkout rather than multiplying the GPU rate alone.

Vagon is a good fit when you want to use a cloud workstation without becoming its cloud administrator. It is not the right recommendation for multi-node model training, Kubernetes-based ML infrastructure, or serverless inference.

Small companies that need centrally managed seats can also consider Vagon Teams. It adds computer assignment, permissions, templates, individual and shared files, usage monitoring, and monthly computer plans. A solo creator probably doesn't need those controls, but a studio managing freelancers or remote artists might.

Amazon WorkSpaces: managed desktops for AWS organizations

Amazon WorkSpaces provides persistent managed desktops with Windows and Linux options. Organizations can connect WorkSpaces to their AWS networking and identity setup, choose from available bundles, and use either an AlwaysOn model or an AutoStop model that combines a monthly base with hourly use.

It can be a sensible option for a company already operating in AWS. It is less appealing when a solo artist simply wants to open a browser and start using a creative app. Directory setup, bundle selection, storage, operating system choices, protocol support, GPU availability, and regional pricing all affect the result.

The Amazon WorkSpaces pricing page doesn't reduce cleanly to one representative number. A fair estimate needs a region, bundle, running mode, storage, OS, and expected monthly hours.

Azure Virtual Desktop: more control for Microsoft-focused IT teams

Azure Virtual Desktop supports personal or pooled Windows 10 and Windows 11 desktops, Windows Server session hosts, custom images, and multi-session deployments. Microsoft manages the control plane, while the customer manages session hosts, applications, identity, governance, and the Azure resources they consume.

The platform suits companies that need policy control, Microsoft identity integration, pooled desktops, or a tailored VDI architecture.

The trade-off is operational effort. Azure Virtual Desktop pricing depends on VM size, storage, networking, licensing eligibility, scaling behavior, and region. It can be efficient when an IT team designs it around a known user pattern. It isn't a simple drop-in replacement for someone who doesn't want to manage VDI.

Shadow PC Pro: monthly Windows access with fixed tiers

Shadow PC provides a full Windows 11 cloud computer rather than only a game catalog. Its Pro tiers mention creative software, real-time 3D, rendering, CUDA or RTX workflows, user management, and longer sessions.

The monthly subscription can appeal to people who expect to use the computer heavily and prefer a fixed tier. The compromises are less flexible hardware selection and a restricted country list. Shadow currently supports the continental United States, Canada, and a defined group of European countries. Hardware, plan names, and prices also differ by market.

For an individual creative professional, the practical choice is straightforward. Choose Vagon when ease of setup, workload-based performance changes, and active usage pricing match your work pattern. Choose AWS or Azure when organizational controls and cloud integration matter more than simplicity. Consider Shadow when a fixed monthly Windows PC is more important than flexible configuration and the service is available in your country.

Which Paperspace alternatives fit GPU compute and AI?

An AI workload needs a different shortlist. First decide whether you want a managed notebook, a persistent development environment, a raw GPU VM, serverless inference, or a multi-GPU training cluster.

Runpod for selectable GPU compute

Runpod offers GPU Pods, Serverless workers, and cluster options across many GPU types. Its public page displays per-hour and per-second pricing, which makes initial comparison easier than providers that require a calculator for every configuration.

Runpod is well suited to developers comfortable with Linux, containers, templates, and their own environment setup. It can cover interactive development, training, batch work, and inference without pretending to be a managed Windows creative desktop.

Storage is separate from GPU runtime. Runpod lists container disk, volume disk, standard network storage, and high-performance network storage as distinct products with different prices and persistence behavior. A low GPU rate can stop looking low if a large volume sits idle for weeks, so include storage in the comparison.

DigitalOcean GPU Droplets for the wider DigitalOcean platform

DigitalOcean GPU Droplets are the natural place to look if you are a new DigitalOcean customer and want Linux GPU infrastructure connected to the rest of its cloud. They can work with DigitalOcean storage, networking, databases, Kubernetes, and other services.

They are not the same product as Paperspace Machines. Paperspace currently stops Machine compute charges when a machine is powered off, while attached storage and add-ons continue. DigitalOcean Droplets are billed while the Droplet exists, even when it is powered off, because the resources remain reserved. Destroying a Droplet ends compute billing, but storage, snapshots, or other retained resources can still have their own charges.

Transfer rules differ too. Paperspace currently says it doesn't charge Machine ingress or egress. DigitalOcean Droplets include an outbound transfer allowance, with additional outbound data billed under DigitalOcean's bandwidth rules. That distinction matters when moving large datasets or streaming a desktop for many hours.

AWS EC2 for infrastructure breadth and control

AWS EC2 offers many accelerated-computing instance families, global cloud integration, automation, security controls, and several purchasing models. On-demand, Spot, Savings Plans, and longer commitments can each fit a different workload.

The flexibility comes with more decisions. GPU family, region, licensing, EBS storage, snapshots, outbound transfer, interruption tolerance, quotas, and support all affect cost and availability. EC2 makes sense for teams that already understand AWS or need its surrounding services. It is rarely the shortest route to a usable creative desktop.

Paperspace Gradient may still be the right answer

A search for an alternative doesn't mean a switch is automatically necessary. Paperspace Gradient still offers browser-based Jupyter notebooks, templates, shared persistent storage, collaboration, and accelerated machines.

Gradient has a free plan with limited free notebook machine access. That doesn't make Paperspace a free general-purpose GPU computer. Paid instances outside the included free types are billed separately, free instances have availability and runtime constraints, and storage above the plan allowance costs extra. Current pricing lists 5 GB included with Free, 15 GB with Pro, and 50 GB with Growth, with additional storage at $0.29 per GB per month.

Vagon only belongs in this part of the discussion when an AI workflow also needs an interactive Windows desktop, local visualization, generative-media tools, or other GUI applications. For containerized training, serverless endpoints, or distributed compute, use an infrastructure platform built for that job.

Are Parsec, Shadow, and cloud gaming services real replacements?

They can be, but only when they replace the layer you actually need.

Parsec is remote access software. It streams a computer you already own or a cloud VM that you rent elsewhere. Parsec no longer provides cloud machines itself, so the total setup still needs a host, GPU, operating system, disk, networking, security, and any relevant cloud charges.

That can work well for a studio with powerful office workstations or a technical user building a cloud VM. It isn't equivalent to buying a managed cloud computer where those pieces arrive together.

Shadow covers more of the stack. It supplies a persistent Windows cloud PC, storage, and the streaming client. That makes it a closer Paperspace replacement for gaming, mods, launchers, and some creative work. Its limits include supported countries, fixed hardware tiers, session policies, and possible incompatibility with games that use certain anti-cheat systems.

NVIDIA GeForce NOW takes another approach. It streams supported games rather than giving the user a normal Windows desktop. The experience can be much simpler for gaming, but you cannot treat it as a workstation for Blender, CAD, video editing, arbitrary development tools, or general file management.

Free cloud gaming also needs careful wording. A free membership may involve queues, shorter sessions, a limited catalog, ads, or regional restrictions. It isn't a permanently free cloud workstation, and the game may still need to be owned through a supported store.

If gaming and professional work overlap, a full cloud computer such as Vagon or Shadow offers more freedom than a catalog service. If gaming is the only goal and the required titles are supported, GeForce NOW may be the simpler and less expensive category. Heavy daily use can also favor a monthly plan, while occasional creative sessions may fit active-hour pricing better.

How do you compare the real cost?

The advertised GPU rate is only one line in the bill. Use this model instead:

Real monthly cost = active compute + persistent storage + snapshots or backups + data transfer + networking or public IPs + Windows or software licensing + platform subscription + support

Paperspace's current pricing shows why this matters. Machine compute stops when the machine is off, but attached storage, public IPs, and other add-ons keep accruing charges until they are destroyed. Paperspace Machines currently include ingress and egress, while Gradient follows separate plan, storage, and compute rules.

Vagon combines the selected active performance rate with the applicable storage or plan component. This structure can work well for someone who edits, renders, or builds in short bursts and doesn't need a high-end GPU running all day. Someone using a cloud PC for eight hours every weekday should also compare a flat monthly provider.

Runpod separates compute from persistent and network storage. AWS and Azure add more variables, including disk type, outbound data, licensing, identity services, support, and the way the environment starts and stops. Their calculators are more useful than a generic list price once you know the exact region and configuration.

Before comparing providers, write down three numbers:

1. Active hours per month

2. Persistent storage required

3. Data that will leave the provider

Then add the software and OS requirements. A Windows video-editing workstation with 500 GB of active media is not financially comparable to a Linux training container that downloads a dataset, runs for six hours, and is deleted.

Treat free offers separately. Gradient has a permanent free plan, but its free machine access is limited. GeForce NOW may have a constrained free membership depending on the region. Signup credits and trials expire, may exclude some GPU products, and shouldn't be described as a free service. Don't plan a production workflow around a promo code unless it is published by the provider and active at checkout.

How do you migrate without losing files or budget control?

Start with an inventory of the current Paperspace environment:

• Operating system and account creation date

• Applications, plugins, and cloud-hosting license rights

• GPU model and VRAM, CPU, and RAM

• Used disk space, snapshots, and backup locations

• Region and measured latency

• Average active hours per month

• Public IPs, networking, and API dependencies

Next, decide whether you need a desktop or only compute. If the work depends on Windows GUI applications, drawing tablets, color accuracy, audio, multiple monitors, or interactive 3D, test those features directly. A successful CUDA command doesn't prove that a remote desktop will feel good during an editing session.

Export files before canceling anything. Paperspace documents transfers through FileZilla, RDP, SCP, and wget. For transfers larger than 10 GB, its guidance recommends copying rather than moving the source, verifying the copy with checksums, and deleting the original only after validation.

Choose a region near the people using the desktop, not merely near the company's billing address. Test with the actual laptop, monitor, network, and peripheral setup. Check latency, resolution, frame rate, text clarity, chroma quality, audio, tablet input, and the time needed to move a representative project.

Run one real project from start to finish. Confirm that the application license permits cloud or virtual-machine use. Set auto-stop behavior, budget alerts, storage limits, and deletion rules before expanding the pilot.

For a creative Windows workflow, the lowest-friction test is usually a managed workstation. Create the new computer, select the nearest available region, install or preselect the required applications, copy a noncritical project, and compare the experience before moving production files. For Runpod, DigitalOcean, AWS, or Azure, plan for infrastructure recreation rather than a simple desktop transfer.

Frequently Asked Questions

Is Paperspace shutting down?

No current official evidence supports that claim. Existing users can still access Paperspace products through the Paperspace Cloud Console, and DigitalOcean says core Paperspace products remain available. New users are increasingly directed toward DigitalOcean's newer AI portfolio.

Is Paperspace free?

Gradient offers a free plan and limited free notebook machine access. Paid instances, extra storage, Core Machines, and other resources can still generate charges. It isn't a free persistent Windows cloud PC.

Can a new user create a Windows Paperspace machine?

Not through the retired Windows template offering. Official documentation says those templates are unavailable to users who joined on or after July 1, 2024. Earlier users remain grandfathered.

Is AWS cheaper than Paperspace?

It can be for a specific workload, purchasing model, and region, but there is no universal answer. Include the GPU instance, Windows if needed, EBS storage, snapshots, outbound transfer, idle behavior, and administration time.

Is Parsec a Paperspace alternative?

Only for remote access. Parsec needs a separate computer, whether that is hardware you own or a cloud VM you rent.

Is Shadow a Paperspace alternative?

It can replace a full Windows PC and gaming workflow in supported countries. It doesn't replace Gradient notebooks, flexible Linux GPU infrastructure, or distributed AI training.

What should a creative Paperspace user try first?

If your work depends on a persistent Windows desktop for Blender, Adobe, Autodesk, Unreal Engine, or similar applications, start with the option that removes the most setup work. Create a Vagon Cloud Computer and check the available performance options, then test one representative project in the nearest available region before moving your production files.