> For the complete documentation index, see [llms.txt](https://docs.parasail.io/parasail-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.parasail.io/parasail-docs/quickstart/dedicated.md).

# Dedicated Instances

Deploy a private GPU endpoint with full control over the model, hardware, and scaling. Dedicated instances are ideal for production workloads, custom models, and models not available on serverless.

## 1. Get an API key

1. Go to <https://www.saas.parasail.io/keys>.
2. Click **Create API Key**.
3. Copy the key—it's shown only once.

## 2. Navigate to the Dedicated tab

In the Parasail dashboard, click the **Dedicated** tab to open the deployment configuration page.

## 3. Configure your deployment

| Field                     | Description                                                                                                                             |
| ------------------------- | --------------------------------------------------------------------------------------------------------------------------------------- |
| **Deployment Name**       | A name for your endpoint.                                                                                                               |
| **HuggingFace ID / URL**  | The model to load. For example, `neuralmagic/Qwen2-72B-Instruct-FP8` or the full HuggingFace URL.                                       |
| **HuggingFace Token**     | Required only for private HuggingFace repos. See [Private HuggingFace Models](/parasail-docs/products/overview-1/private-hf-models.md). |
| **Hardware Service Tier** | Choose from low-cost, low-latency, or ultra-low-latency GPU configurations.                                                             |

If the model is supported, you'll see a green confirmation message.

## 4. (Optional) Set advanced options

* **Speculative Decoding Draft Model**—speed up output with a draft model. See [Speculative Decoding](/parasail-docs/products/overview-1/speculative-decoding.md).
* **Replicas**—spin up multiple load-balanced replicas for high throughput.
* **Scale Down Policy**—automatically shut down after idle time to avoid unexpected costs.
* **Max Concurrent Connections**—set a per-replica concurrency limit to maintain QoS.

## 5. Deploy

Click **Deploy**. If the model weights have been cached previously, deployment takes 3–5 minutes. If weights need to be downloaded from HuggingFace, it can take 10 minutes to several hours depending on model size.

## 6. Call your endpoint

Once the endpoint is live, call it using the OpenAI SDK:

```python
import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.parasail.io/v1",
    api_key=os.environ["PARASAIL_API_KEY"],
)

response = client.chat.completions.create(
    model="your-deployment-name",
    messages=[{"role": "user", "content": "Hello!"}]
)

print(response.choices[0].message.content)
```

## Next steps

* [Dedicated instances overview](/parasail-docs/products/overview-1.md)—full guide to dedicated endpoints
* [Auto-scaling](/parasail-docs/products/overview-1/auto-scaling.md)—scale replicas with traffic
* [FP8 quantization](/parasail-docs/products/overview-1/fp8-quantization.md)—reduce cost with quantization
* [Management API](/parasail-docs/products/overview-1/management-api.md)—manage endpoints programmatically