***
title: Launchables
description: >-
Learn about NVIDIA Brev Launchables - one-click deployable GPU environments
that bundle hardware, software, and code.
-----------------------------------------
Launchables bundle GPU hardware, software environments, and code into one-click deployable packages. Share a link, and anyone can spin up an identical environment.
## What are Launchables?
A Launchable is a reproducible, shareable GPU environment configuration. It captures everything needed to run a specific workload:
* **Hardware requirements:** GPU type, memory, disk space
* **Software stack:** Base image, dependencies, setup scripts
* **Code:** Git repository, notebooks, or embedded files
* **Networking:** Exposed ports, Jupyter settings
**Use cases:** Tutorials, demos, workshops, team onboarding, reproducing research, and distributing GPU applications.
## Creating a Launchable
Create a Launchable in the [Brev Console](https://brev.nvidia.com) using the a step-by-step wizard.
### Step 1: Files and Runtime
Choose how to add code files and select a runtime mode for your Launchable:
**Code source:**
| Option | Description | Best for |
| ------------------------- | ---------------------------------------------- | ------------------------------- |
| **Git Repository** | Link a public repository URL or notebook link. | Open-source projects, tutorials |
| **Embedded in Container** | Code is already in the container image. | Custom Docker images |
| **No Code** | Empty GPU sandbox environment. | Exploration, ad-hoc work |
**Runtime mode:**
| Mode | Description |
| ------------- | ------------------------------------------------------------------------------------ |
| **VM Mode** | Run directly on the GPU VM with Ubuntu 22.04. Docker, Python, and CUDA preinstalled. |
| **Container** | Run in a Docker container or Docker Compose stack. |
**Private Repositories**: If you need to pull from a private registry or require API keys, select **VM Mode** runtime and handle authentication in a setup script.
### Step 2: Configure Environment
This step changes based on the runtime mode selected in Step 1:
You are prompted: **Do you want to run a setup script?**
* Upload or paste a bash setup script to customize the environment (install dependencies, configure services)
* Full SSH access to the instance
You are prompted: **Choose a Container Configuration**
* **Featured Containers**: Prebuilt images for common AI/ML frameworks (recommended for simple demos)
* **Docker Compose**: For complex, multi-container workflows
* If using Docker Compose, validate your configuration before proceeding
### Step 3: Jupyter and Networking
Configure access and networking:
**Jupyter Notebook Experience**:
* **Yes**: NVIDIA Brev installs Jupyter on the host and provides a one-click button to access code through JupyterLab.
* **No**: Users access the instance with SSH using the Brev CLI.
**Network Configuration**:
* **Secure Links**: Preconfigure Cloudflare tunnel URLs for specific ports.
* **TCP/UDP Ports**: Specify ports and assign access permissions.
### Step 4: Compute Configuration
Select hardware for your Launchable:
1. Choose an **NVIDIA GPU** based on your workload requirements.
2. Filter by VRAM, cloud provider, compute attributes, or price.
3. Adjust **disk storage** based on data and model size needs.
Select the minimum-cost configuration that meets your requirements. Users choose different hardware when deploying, if needed.
### Step 5: Final Review
Complete your Launchable:
1. Enter a **Name** for your Launchable.
2. Set **View Access** to control who can see and deploy your Launchable:
* **Publish to community** toggle. Turn on to make the Launchable discoverable by all users in the Explore search results.
* With the toggle off, choose between **Anyone with the link** (default) or **Only my organization**.
3. **Preview** the deployment page to see what users will experience.
4. Click **Create Launchable** to generate your shareable link.
## Runtime Modes
Choose how your Launchable configures the instance environment:
Run directly on the instance with setup scripts. Best for simple configurations and when you need full VM access.
* Bash setup scripts
* apt/pip dependencies
* Full SSH access
Run in a Docker container or Docker Compose stack. Best for reproducible, isolated environments.
* Custom Dockerfiles
* Docker Compose stacks
* Prebuilt images (NGC, Docker Hub)
## Exploring Launchables
The **Launchables** tab in the [Brev Console](https://brev.nvidia.com) provides a fully indexed, searchable collection of shared launchables. Browse curated picks or search to find GPU environment templates you can deploy with one click.
### Browsing
When you open the **Explore** view within the **Launchables** tab, the page displays curated sections:
* **Featured**: Hand-picked launchables highlighted with a blue badge (up to six shown).
* **Trending This Week**: Popular launchables ranked by recent activity (up to three shown, with green rank badges).
* **All Time Popular**: Most popular launchables overall (up to six shown, with yellow rank badges).
Each launchable card displays: name, author, description, cost per hour, view count, and deploy count. Click any card to go directly to the deploy page.
A row of cloud provider logos shows available compute backing (AWS, Google Cloud, Crusoe, Lambda, Nebius, Hyperstack, Oracle, and others).
### Searching and Filtering
The search bar accepts free-text queries across launchable names, containers, models, workflows, and GPUs. Press **Enter** or click the search icon to execute.
Two optional filters narrow results further:
| Filter | Description |
| ------------------ | ---------------------------------------------------------------------------------- |
| **GPU Name** | Filter by specific GPU type (dynamically populated from available instance types). |
| **Cloud Provider** | Filter by cloud provider, such as AWS or GCP. |
Changing a filter triggers an immediate search. Active filters appear as dismissible badges below the search bar. Click **Clear all** to reset and return to the curated browse view.
Results display in a responsive grid with infinite scroll (results load automatically as you scroll).
You can deep-link to filtered results by adding query parameters: `?gpuType=A100` or `?cloud=AWS`. This is useful for embedding links in documentation or READMEs that take users directly to relevant launchables.
### Sharing and Access Levels
Control who can view and deploy your launchables with three access levels:
| Access Level | Visibility | Use Case |
| ---------------- | ---------------------------------------------------- | ----------------------------------------- |
| **Organization** | Only members of your organization. | Team collaboration, internal tools |
| **Link sharing** | Anyone with the direct link. | Workshops, selective distribution. |
| **Published** | Discoverable by all users in Explore search results. | Open-source projects, community resources |
Set visibility during creation in the final review step, or change it later from the **My Launchables** tab. New launchables default to **Anyone with the link**. To make a launchable discoverable in Explore, turn on **Publish to community**.
## Managing Launchables
All your Launchables display under the **Launchables** tab. From there, you can:
| Action | Description |
| ----------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| **View Metrics** | See views and deployment counts for each Launchable. |
| **Change Access** | Change visibility between Organization, Link sharing, and Published. Switching to Published opens a publish confirmation; switching away from Published shows an unpublish warning that the Launchable will no longer display in search results. |
| **Preview** | See the deployment page that users will experience. |
| **Copy Markdown Badge** | Embed a "Launch on Brev" button in READMEs and documentation. |
| **Show Configuration** | View hardware and software details. |
| **Delete** | Permanently remove a Launchable. |
### Embedding Launchables
Add a launch badge to any markdown file to let users deploy with one click:
```markdown
[](https://brev.nvidia.com/launchable/deploy?launchableID=your-launchable-id)
```
## What's Next
Learn about preconfigured software environments.
Run Docker workloads with GPU access.