Best Cloud GPU Providers for Visual Studio Code

Compare the Top Cloud GPU Providers that integrate with Visual Studio Code as of September 2025

This a list of Cloud GPU providers that integrate with Visual Studio Code. Use the filters on the left to add additional filters for products that have integrations with Visual Studio Code. View the products that work with Visual Studio Code in the table below.

What are Cloud GPU Providers for Visual Studio Code?

Cloud GPU providers offer scalable, on-demand access to Graphics Processing Units (GPUs) over the internet, enabling users to perform computationally intensive tasks such as machine learning, deep learning, scientific simulations, and 3D rendering without the need for significant upfront hardware investments. These platforms provide flexibility in resource allocation, allowing users to select GPU types, configurations, and billing models that best suit their specific workloads. By leveraging cloud infrastructure, organizations can accelerate their AI and ML projects, ensuring high performance and reliability. Additionally, the global distribution of data centers ensures low-latency access to computing resources, enhancing the efficiency of real-time applications. The competitive landscape among providers has led to continuous improvements in service offerings, pricing, and support, catering to a wide range of industries and use cases. Compare and read user reviews of the best Cloud GPU providers for Visual Studio Code currently available using the table below. This list is updated regularly.

  • 1
    JarvisLabs.ai

    JarvisLabs.ai

    JarvisLabs.ai

    We have set up all the infrastructure, computing, and software (Cuda, Frameworks) required for you to train and deploy your favorite deep-learning models. You can spin up GPU/CPU-powered instances directly from your browser or automate it through our Python API.
    Starting Price: $1,440 per month
  • 2
    Apolo

    Apolo

    Apolo

    Access readily available dedicated machines with pre-configured professional AI development tools, from dependable data centers at competitive prices. From HPC resources to an all-in-one AI platform with an integrated ML development toolkit, Apolo covers it all. Apolo can be deployed in a distributed architecture, as a dedicated enterprise cluster, or as a multi-tenant white-label solution to support dedicated instances or self-service cloud. Right out of the box, Apolo spins up a full-fledged AI-centric development environment with all the tools you need at your fingertips. Apolo manages and automates the infrastructure and processes for successful AI development at scale. Apolo's AI-centric services seamlessly stitch your on-prem and cloud resources, deploy pipelines, and integrate your open-source and commercial development tools. Apolo empowers enterprises with the tools and resources necessary to achieve breakthroughs in AI.
    Starting Price: $5.35 per hour
  • 3
    Thunder Compute

    Thunder Compute

    Thunder Compute

    Thunder Compute is a cloud platform that virtualizes GPUs over TCP, allowing developers to scale from CPU-only machines to GPU clusters with a single command. By tricking computers into thinking they're directly attached to GPUs located elsewhere, Thunder Compute enables CPU-only machines to behave as if they have dedicated GPUs, while the physical GPUs are actually shared among several machines. This approach improves GPU utilization and reduces costs by allowing multiple workloads to run on a single GPU with dynamic memory sharing. Developers can start by building and debugging on a CPU-only machine and then scale to a massive GPU cluster with just one command, eliminating the need for extensive configuration and reducing the costs associated with paying for idle compute resources during development. Thunder Compute offers on-demand access to GPUs like NVIDIA T4, A100 40GB, and A100 80GB, with competitive rates and high-speed networking.
    Starting Price: $0.27 per hour
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