# Deploy your first model

> On the Endpoints page, select New endpoint, type a model name such as qwen3:8b, select Check model, then Create and start.

Source: https://bitsrun.com/docs/get-started/first-endpoint/
Updated: 2026-11-09

An endpoint is your private address for one model. Creating one takes a minute; the first start takes a few more while a GPU boots and loads the model (never billed).

## In the dashboard

1. Select **Endpoints**, then **New endpoint**.
2. In **Model**, type `qwen3:8b`. Any [Ollama name or Hugging Face repo](https://bitsrun.com/docs/models/) works.
3. Select **Check model**. BitsRun reads the model's size and shows what it needs.

![The New endpoint form with an empty model field, a Check model button and an upload option](https://bitsrun.com/docs/img/new-endpoint-form.png "The New endpoint form before you check a model.")

4. Read the green box. For `qwen3:8b` it says the model has 5.2 GB of weights, fits an NVIDIA L4, runs on llama.cpp and remembers up to 40,960 tokens.
5. Leave **GPU** on the suggested size. BitsRun picks the cheapest GPU that fits.
6. Optional: give it a **Name**, such as "Support chat".
7. Optional: change **Sleep after**. The default is 2 minutes without requests.
8. Keep **Start it now** ticked if you want to use it right away, then select **Create and start**.

![The New endpoint form after checking qwen3:8b, showing it fits an NVIDIA L4 with 40,960 tokens of context, the GPU, name and sleep settings, and a Create and start button](https://bitsrun.com/docs/img/new-endpoint-checked.png "After Check model: the size, the GPU it fits, the price and the start-up time.")

The new card shows each start step: getting a GPU machine ready, downloading the model, loading it into GPU memory, then **Running: answering requests now**.

![An endpoint card with its status, model type, size, GPU, price, sleep time, its URL with a Copy button, and Start, Settings, Performance and Delete buttons](https://bitsrun.com/docs/img/endpoint-card.png "An endpoint card. Copy the URL from the dark bar.")

## From the terminal

```bash
curl -fsSL https://get.bitsrun.com | sh
bitsrun login
bitsrun deploy qwen3:8b --name "Support chat" --key
```

On macOS and Linux the installer puts `bitsrun` in `~/.local/bin`. If that folder is not on your PATH yet, it prints the one line to add it. Run that line and open a new terminal before `bitsrun login`.

`--key` also creates an API key that only works with this endpoint and prints it once. See [Command line](https://bitsrun.com/docs/cli/).

## Words in the form

- **Context (memory length):** how much text the model can read at once, counted in tokens. A token is about three quarters of an English word.
- **llama.cpp, vLLM, Text Embeddings Inference:** the programs (runtimes) that run the model on the GPU. BitsRun picks one from the model's format.
- **Sleep after:** how long the endpoint stays awake after the last request. It is billed while awake, so short is cheaper; long avoids waiting for a wake.

## What can go wrong

| Message | What to do |
|---|---|
| "We could not find that model." | Check the spelling and tag, for example `qwen3:8b` not `qwen3-8b`. For Hugging Face, check the owner and repo name. |
| "This model is larger than the biggest GPU size we offer today." | Pick a smaller model or a more compressed version. See [Quantization](https://bitsrun.com/docs/models/quantization/). |
| "Your plan allows no more endpoints." | Delete one you no longer use, or move to a bigger plan. Pay-as-you-go allows 2 endpoints. |
| "Created, but not started: check your credit, then press Start." | Your balance is $0. [Add credit](https://bitsrun.com/docs/get-started/add-credit/), then select **Start** on the card. |

More reasons are in [Models that cannot be deployed](https://bitsrun.com/docs/models/unsupported/).

## Next step

[Call your endpoint](https://bitsrun.com/docs/get-started/call-your-endpoint/).