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

# Qwen3 VL 2B - Instruct

> Vision-language model, 256K context

<CardGroup cols={1}>
  <Card title="Try Qwen3 VL 2B - Instruct in the Workbench" icon="flask" href="https://www.oxen.ai/ai/workbench?model=qwen3-vl-2b-instruct">
    Run this model interactively, tune parameters, and compare outputs.
  </Card>
</CardGroup>

**Model ID:** `qwen3-vl-2b-instruct`

Qwen/Qwen3-VL-2B-Instruct is a **multimodal LLM** that excels at lightweight vision‑language tasks such as visual question answering, document and UI understanding, and general image‑grounded chat, while being small enough for edge or resource‑constrained environments.

Some other noteworthy use cases of Qwen/Qwen3-VL-2B-Instruct include **OCR and document analysis across many languages**, and **agentic interactions that involve interpreting screen content or layouts before deciding on actions**.

| Metric             | Value          |
| ------------------ | -------------- |
| Parameter Count    | 2 billion      |
| Mixture of Experts | No             |
| Context Length     | 256,000 tokens |
| Multilingual       | Yes            |
| Quantized\*        | No             |

\**Quantization is specific to the inference provider and the model may be offered with different quantization levels by other providers.*

## Example request

<Tip>
  Use the [Workbench](https://www.oxen.ai/ai/workbench?model=qwen3-vl-2b-instruct) as a request builder: configure parameters for this model in the UI, then open the **API** tab to copy the exact cURL or Python call.
</Tip>

<Tabs>
  <Tab title="Minimal">
    <CodeGroup>
      ```bash cURL theme={null}
      curl -X POST https://hub.oxen.ai/api/ai/chat/completions \
        -H "Content-Type: application/json" \
        -H "Authorization: Bearer $OXEN_API_KEY" \
        -d '{
        "model": "qwen3-vl-2b-instruct",
        "messages": [
          {
            "role": "user",
            "content": "Hello, what can you do?"
          }
        ]
      }'
      ```

      ```python Python theme={null}
      import os
      import requests

      response = requests.post(
          "https://hub.oxen.ai/api/ai/chat/completions",
          headers={
              "Content-Type": "application/json",
              "Authorization": f"Bearer {os.environ['OXEN_API_KEY']}",
          },
          json={
              "model": "qwen3-vl-2b-instruct",
              "messages": [
                  {
                      "role": "user",
                      "content": "Hello, what can you do?"
                  }
              ]
          },
      )
      response.raise_for_status()
      print(response.json())
      ```
    </CodeGroup>
  </Tab>

  <Tab title="Basic parameters">
    <CodeGroup>
      ```bash cURL theme={null}
      curl -X POST https://hub.oxen.ai/api/ai/chat/completions \
        -H "Content-Type: application/json" \
        -H "Authorization: Bearer $OXEN_API_KEY" \
        -d '{
        "model": "qwen3-vl-2b-instruct",
        "messages": [
          {
            "role": "user",
            "content": "Hello, what can you do?"
          }
        ],
        "temperature": 0.7,
        "max_tokens": 1024,
        "stream": false
      }'
      ```

      ```python Python theme={null}
      import os
      import requests

      response = requests.post(
          "https://hub.oxen.ai/api/ai/chat/completions",
          headers={
              "Content-Type": "application/json",
              "Authorization": f"Bearer {os.environ['OXEN_API_KEY']}",
          },
          json={
              "model": "qwen3-vl-2b-instruct",
              "messages": [
                  {
                      "role": "user",
                      "content": "Hello, what can you do?"
                  }
              ],
              "temperature": 0.7,
              "max_tokens": 1024,
              "stream": false
          },
      )
      response.raise_for_status()
      print(response.json())
      ```
    </CodeGroup>
  </Tab>

  <Tab title="All parameters">
    <CodeGroup>
      ```bash cURL theme={null}
      curl -X POST https://hub.oxen.ai/api/ai/chat/completions \
        -H "Content-Type: application/json" \
        -H "Authorization: Bearer $OXEN_API_KEY" \
        -d '{
        "model": "qwen3-vl-2b-instruct",
        "messages": [
          {
            "role": "user",
            "content": "Hello, what can you do?"
          }
        ],
        "temperature": 0.7,
        "max_tokens": 1024,
        "stream": false,
        "top_p": 1.0
      }'
      ```

      ```python Python theme={null}
      import os
      import requests

      response = requests.post(
          "https://hub.oxen.ai/api/ai/chat/completions",
          headers={
              "Content-Type": "application/json",
              "Authorization": f"Bearer {os.environ['OXEN_API_KEY']}",
          },
          json={
              "model": "qwen3-vl-2b-instruct",
              "messages": [
                  {
                      "role": "user",
                      "content": "Hello, what can you do?"
                  }
              ],
              "temperature": 0.7,
              "max_tokens": 1024,
              "stream": false,
              "top_p": 1.0
          },
      )
      response.raise_for_status()
      print(response.json())
      ```
    </CodeGroup>
  </Tab>
</Tabs>

## Fetch model details

The [models endpoint](/inference-api/reference/models/overview) returns the full model object, including its `json_request_schema`.

```bash theme={null}
curl -H "Authorization: Bearer $OXEN_API_KEY" https://hub.oxen.ai/api/ai/models/qwen3-vl-2b-instruct
```

## Request parameters

This model follows the standard OpenAI chat completions request body. See the [chat completions reference](../inference-api.mdx) for the full parameter list.