# System Specifications

MOTAR is lightweight and highly portable; it can run on hardware ranging from a Raspberry Pi to a full cloud-based cluster. The core system has a minimal footprint, but performance will depend on:

* Number of **concurrent users**
* **Asset storage** needs (models, images, audio)
* **Bandwidth** and **RAM** availability

Choose the appropriate setup based on your use case:

#### Portable / Development (Minimum Viable)

*Example: Raspberry Pi 5*

* **CPU:** 2.4GHz ARM 64-bit quad-core
* **RAM:** 8–16GB DDR4
* **Storage:** 128–250GB SSD (external preferred)
* **Network:** Gigabit Ethernet or strong WiFi

✅ Good for: portable, single-user instances.

***

#### Desktop / Local Server (Recommended)

*Suitable for small teams or internal use*

* **CPU:** AMD/Intel 64-bit, 4–8 cores
* **RAM:** 16–32GB
* **Storage:** 250GB+ SSD
* **Network:** Wired Ethernet or reliable WiFi
* **Additional:** Virtualization must be enabled on the system

✅ Balanced setup for moderate asset use and 1–10 concurrent users.

***

#### Cloud / Production (Scalable Infrastructure)

*For high concurrency and asset-heavy environments*

* **CPU:** 16+ core AMD/Intel/ARM (x86\_64)
* **RAM:** 64GB+ (scale based on users)
* **Storage:** 1TB+ SSD or expandable volume
* **Network:** High-throughput, low-latency

✅ Supports **Kubernetes with autoscaling nodes** for dynamic performance under load.

***

> 💡 **Tip:** While MOTAR itself is lightweight, your assets and users will dictate the scale. Plan ahead for growth in RAM, storage, and bandwidth.


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.motar.com/hardware-requirements/system-specifications.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.