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

# Machines

> Review the GPU hardware allocated to your organization and how much of it is still free.

![Acasia Developer Portal Machines page showing one active NVIDIA H200 bare-metal machine with two clusters](https://docs.acasia.com/assets/portal-machines-BPlqRyB4.png)

Machines are allocated to your organization by Acasia — you can't create or remove them yourself. A machine may represent:

* A single GPU server
* A DGX-class multi-GPU system
* A rented GPU instance
* A partner-supplied host
* Another GPU-backed runtime environment

## Machine fields

| Field     | Description                                   |
| --------- | --------------------------------------------- |
| Name      | Machine identifier                            |
| Type      | Hardware category (e.g., Bare Metal)          |
| Status    | Operational state of the machine              |
| GPU       | GPU model (e.g., NVIDIA H200)                 |
| GPU Count | Number of GPUs available on the machine       |
| CPU       | CPU model and core count                      |
| RAM       | Total memory                                  |
| Storage   | Total storage capacity                        |
| Network   | Network speed                                 |
| Clusters  | Clusters created from this machine's capacity |

## Machine vs. cluster

A machine is the underlying hardware. A cluster is a deployable allocation carved from that hardware. One machine can host multiple clusters, each with its own slice of GPU, CPU, RAM, and storage.

You create and manage clusters — not machines. Machines are managed by Acasia and appear in your portal once allocated.

## Clusterization

Some machines support **clusterization** — the ability to split a single machine's resources into multiple independent clusters. This allows different teams, workloads, or projects to use isolated compute environments on the same physical hardware.

When a machine supports clusterization:

* Multiple clusters can be created from the same machine
* Each cluster has its own resource allocation (GPU, CPU, RAM, storage)
* Clusters operate independently

When a machine does not support clusterization, it maps one-to-one with a single cluster.

## Machine status

| Status      | Meaning                                                      |
| ----------- | ------------------------------------------------------------ |
| Active      | Machine is operational and available for cluster creation    |
| Inactive    | Machine is registered but not currently active               |
| Maintenance | Machine is undergoing maintenance — clusters may be affected |
| Out of Sync | Acasia Cloud and the runtime environment do not match        |

## Capacity planning

Key questions:

* How many GPUs does the machine have?
* How many clusters already exist on this machine?
* Does the remaining capacity support the planned workload?

If your organization has exhausted available machine capacity, contact Acasia to request additional allocation.