NVIDIA AI Workbench

What it does

NVIDIA AI Workbench is a desktop environment manager for developers and data scientists working on AI and machine learning projects on GPU systems. You install the Desktop App on Windows, macOS, or Ubuntu, then manage a Git repository as a project. Workbench builds a containerized development environment from versioned configuration files in that repository, and it manages drivers, container toolkit, and runtimes on each machine. Input is your code, data, and configuration; output is a reproducible project environment running on local or remote GPUs.

People use it to prototype and fine-tune models, such as Llama 3, Mistral, or Stable Diffusion XL, and to build RAG chatbots or multi-container applications defined by a compose file. Its distinguishing feature is that the same interface works whether the project runs on a laptop, a cloud instance, or a data center server, and Git changes made inside the project container are surfaced for review. Project containers also let you run IDEs, JupyterLab, or AI coding agents in a sandbox separate from the host.

It suits technical users who need to move GPU workloads between machines and keep environments reproducible. The desktop app and CLI are free to download, but NVIDIA states that support requires an NVIDIA AI Enterprise license, and the homepage points to an NVIDIA hardware and software setup for remote and cloud use. Limitations include the need for NVIDIA GPU hardware for workloads and the requirement to accept the NVIDIA AI Enterprise EULA before installing.

What it can do

• Manage Git repositories as projects with containerized development environments defined by versioned configuration files.
• Run the same workflow locally or on remote systems such as cloud instances, workstations, or servers.
• Automatically manage NVIDIA drivers, container toolkit, builds, and runtimes on each location.
• Run web apps such as JupyterLab and RStudio in the project container and access them through a browser.
• Run AI coding agents in an isolated project container with Git diff review and rollback in the Desktop App.
• Define multi-container full-stack applications with a compose file and share them as repositories.

Works with

• VS Code
• Cursor
• Claude
• GitHub
• GitLab.com

Example workflows

Fine-tune an open LLM locally

Input: a Git project from NVIDIA's example repos and a custom dataset. Steps: clone the project in the Desktop App, let Workbench build the container, run training in the project container, review changes in Git, then scale to a cloud GPU location. Output: a fine-tuned model and committed project changes.

Build and share a RAG chatbot

Input: a RAG project with a compose file and document data. Steps: run the embedding and inference services locally or via a remote endpoint, test the chatbot in the browser, and share the repository with a teammate. Output: a runnable multi-container app the teammate can clone and start.

Before you choose

• Support requires an NVIDIA AI Enterprise license, while the Desktop App is free to use.
• Remote and cloud use depends on the GPU systems you connect; the docs describe remote installation separately.
• Sandboxed agents run inside the project container, so their permissions depend on the settings and hooks you configure.

Listed under

• Coding

Get started

Download for Windows, Install on Ubuntu, or Download for macOS; accept the NVIDIA AI Enterprise EULA.

1. Install the Desktop App for Windows, macOS, or Ubuntu from the NVIDIA download links.
2. Open the Desktop App, add a local or remote location, and clone or create a project.
3. Review the project's .project/spec.yaml and requirements files, then start the project container.

Desktop App and CLI are free to download and use. Enterprise support requires an NVIDIA AI Enterprise license; its price was not captured. Cloud or GPU hardware costs are not covered by this page.

NVIDIA AI Workbench is free to use. See their pricing page ↗

Sources for this overview

Product pages, documentation, and pricing checked 28 Oct 2026. Each source supports part of the overview; availability and prices can change.

• Tools for AI Workstations | NVIDIA ↗www.nvidia.com
• NVIDIA AI Workbench | NVIDIA AI Workbench User Guide ↗docs.nvidia.com

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nvidia.com: product, pricing and policy pages

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knowledge_base

Last checked 28 Oct 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.