> ## Documentation Index
> Fetch the complete documentation index at: https://docs.together.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Overview

> Deploy custom containers on Together's managed GPU infrastructure with automatic scaling, job queues, and built-in observability.

<Note>Custom containers are available through the Together sales team. [Contact sales](https://www.together.ai/forms/contact-sales) to get access.</Note>

<Tip>Using a coding agent? Install the [together-dedicated-containers](https://github.com/togethercomputer/skills/tree/main/skills/together-dedicated-containers) skill to let your agent write correct dedicated container code automatically. [Learn more](/docs/agent-skills).</Tip>

Dedicated Containers let you run your own Dockerized inference workloads on Together's managed GPU infrastructure. You bring the container. Together handles compute provisioning, autoscaling, networking, and observability.

You build and push a Docker image using the [Jig CLI](/docs/deployments-jig). Inside your container, the [Sprocket SDK](/docs/deployments-sprocket) connects your inference code to Together's managed [job queue](/docs/deployments-queue). Once deployed, your workers can receive requests.

* Wrap and deploy your model in 20 minutes
* Boost conversion and margins with fair priority queueing
* Bottomless capacity right before you need it

<Frame>
  <img src="https://mintcdn.com/togetherai-52386018/guu83tcrNiDPEySM/images/dedicatedcontainers.svg?fit=max&auto=format&n=guu83tcrNiDPEySM&q=85&s=1697805b576af1b144ac6f280e829ecc" alt="Dedicated Containers Architecture" width="2357" height="1168" data-path="images/dedicatedcontainers.svg" />
</Frame>

***

## Quickstart

With the [Jig CLI](/docs/deployments-jig), a first deployment is three commands:

```bash theme={null}
# scaffold the jig config next to your inference code
tg beta jig init

# build, push, and deploy the container in one step
tg beta jig deploy

# watch the deployment come up
tg beta jig status
```

<Card title="Deploy Your First Container" icon="rocket" href="/docs/containers-quickstart">
  Deploy your first container from the command line
</Card>

## Concepts

<Card title="Platform Overview" icon="sitemap" href="/docs/together-deployments">
  Architecture, deployment lifecycle, autoscaling, and troubleshooting
</Card>

<CardGroup cols={3}>
  <Card title="Jig CLI" icon="hammer" href="/docs/deployments-jig">
    Build, deploy, secrets, and volumes
  </Card>

  <Card title="Sprocket SDK" icon="code" href="/docs/deployments-sprocket">
    Inference workers with setup() and predict()
  </Card>

  <Card title="Queue API" icon="stack-2" href="/docs/deployments-queue">
    Async jobs with priority and progress
  </Card>
</CardGroup>

## Guides

<CardGroup cols={2}>
  <Card title="Image Generation" icon="photo" href="/docs/dedicated_containers_image">
    Single-GPU Flux2 model
  </Card>

  <Card title="Video Generation" icon="video" href="/docs/dedicated_containers_video">
    Multi-GPU Wan 2.1 with torchrun
  </Card>
</CardGroup>

## Reference

<CardGroup cols={3}>
  <Card title="Jig CLI" icon="terminal" href="/reference/cli/jig">
    CLI commands and pyproject.toml configuration
  </Card>

  <Card title="Sprocket SDK" icon="code" href="/reference/dci-reference-sprocket">
    Base classes, file handling, and error reference
  </Card>

  <Card title="REST API" icon="book" href="/reference/deployments-list">
    Deployments, secrets, storage, and queue
  </Card>
</CardGroup>

***

<Card title="Get Access" icon="mail" href="mailto:support@together.ai">
  Contact your account representative or [support@together.ai](mailto:support@together.ai) to enable Dedicated Containers for your organization.
</Card>