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

# Local Devices

> Run inference on workstations, laptops, and mobile devices

Deploy Subconscious models directly on local hardware for offline inference, ultra-low latency, and complete data privacy. All processing happens on-device, so no data ever leaves the machine.

<CardGroup cols={3}>
  <Card title="Zero latency" icon="bolt">
    Inference runs directly on device with no network round-trip
  </Card>

  <Card title="Fully offline" icon="wifi-slash">
    Works without internet connectivity
  </Card>

  <Card title="Complete privacy" icon="lock">
    Data never leaves the device
  </Card>
</CardGroup>

## Supported Devices

### Workstations & Servers

* Desktop machines with dedicated GPUs
* Development workstations
* Edge servers and on-site hardware

### Laptops

* GPU-equipped laptops (NVIDIA, Apple Silicon)
* Development and field use

### Mobile Devices

* iOS and Android deployment
* On-device inference for mobile applications

## Use Cases

* **Sensitive data processing** for healthcare, legal, and financial documents that cannot leave the device
* **Field operations** where deployments don't have reliable internet access
* **Development** for local testing and iteration without API costs
* **Edge computing** for real-time inference at the point of data collection

## How It Works

We provide optimized model packages for different hardware targets. The local runtime exposes the same OpenAI- and Anthropic-compatible API on localhost, so your application code works unchanged:

<CodeGroup>
  ```python Python (OpenAI) theme={null}
  from openai import OpenAI

  # Same API, running locally
  client = OpenAI(
      api_key="local",
      base_url="http://localhost:8080/v1",
  )

  response = client.chat.completions.create(
      model="subconscious/tim-qwen3.6-27b",
      messages=[{"role": "user", "content": "Hello!"}],
  )
  ```

  ```python Python (Anthropic) theme={null}
  from anthropic import Anthropic

  # Same API, running locally
  client = Anthropic(
      auth_token="local",
      base_url="http://localhost:8080",
  )

  message = client.messages.create(
      model="subconscious/tim-qwen3.6-27b",
      max_tokens=1024,
      messages=[{"role": "user", "content": "Hello!"}],
  )
  ```
</CodeGroup>

<Card title="Get in Touch" icon="phone" href="https://www.subconscious.dev/product/edge-devices/contact">
  Fill out our contact form to discuss local deployment for your organization.
</Card>