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

# Dedicated GPUs

> Source dedicated GPU virtual machines, bare-metal nodes, and private multi-node clusters through Lilac's network.

Lilac helps teams source dedicated GPU capacity when reserved hardware is a better fit than the pay-per-token [serverless inference](/inference/quickstart) network.

## What Lilac offers

Capacity sourced through Lilac's network of GPU providers:

* **Dedicated GPU virtual machines** for reserved workloads.
* **Bare-metal GPU nodes** where full hardware control is required.
* **Private multi-node clusters** for distributed training and larger deployments.

Lilac coordinates sourcing across this network. Underlying machines and facilities are operated by the providers Lilac works with.

## Who it is for

Teams whose workloads require:

* Reserved, non-shared capacity.
* A specific GPU architecture or interconnect.
* Multi-node topology.
* A particular region.
* A defined start date and term.

For workloads that do not require reserved hardware, see [serverless inference](/inference/quickstart).

## How requesting capacity works

<Steps>
  <Step title="Define the requirement">
    Share GPU type, topology, region, start date, and term.
  </Step>

  <Step title="Source qualified options">
    Lilac compares available capacity across its network and surfaces options based on technical and commercial fit.
  </Step>

  <Step title="Coordinate launch">
    Lilac coordinates commercial details, access, and handoff into your environment. Provisioning is not instant or self-service.
  </Step>

  <Step title="Stay supported">
    Lilac remains the point of contact during the deployment and coordinates issues and escalations.
  </Step>
</Steps>

## Pricing and availability

Final pricing and availability depend on configuration, region, start date, and term. Indicative pricing on the marketing site is not a fixed quote and specific hardware is not universally available.

See current indicative options on the [dedicated GPUs page](https://getlilac.com/dedicated-gpus).

## Talk to us

<Card title="Book a call about dedicated GPUs" icon="calendar" href="https://calendly.com/d/ctxy-jd8-585/lilac-support">
  Share the workload, model, throughput, region, and term. We'll come back with options.
</Card>

Or email [contact@getlilac.com](mailto:contact@getlilac.com).

## Related

* [Serverless inference quickstart](/inference/quickstart)
* [Inference pricing](/inference/pricing)
* [Dedicated GPUs marketing page](https://getlilac.com/dedicated-gpus)