# Qwen3.5

Qwen3.5 is Alibaba's vision-language model family. It accepts an image and a text prompt and returns a text response. We support two pretrained checkpoints in Inference:

| Alias          | Parameters |
| -------------- | ---------- |
| `qwen3_5-0.8b` | 0.8B       |
| `qwen3_5-2b`   | 2B         |

{% hint style="info" %}
Qwen3.5 is not available on the Serverless Hosted API. Run it on a [Dedicated Deployment](/deploy/dedicated-deployments.md) or [self-hosted Inference](https://inference.roboflow.com/).
{% endhint %}

## Code sample

Install the [Inference SDK](https://inference.roboflow.com/):

```bash
pip install inference-sdk
```

Set `api_url` to your Dedicated Deployment URL or a local Inference server. Pass your [Roboflow API Key](https://app.roboflow.com/settings/api) via the `API_KEY` environment variable.

```python
import os
import urllib.request
from inference_sdk import InferenceHTTPClient

image_url = "https://media.roboflow.com/notebooks/examples/dog.jpeg"
image_path = "dog.jpeg"
urllib.request.urlretrieve(image_url, image_path)

client = InferenceHTTPClient(
    api_url="https://your-deployment.roboflow.cloud",
    api_key=os.getenv("API_KEY"),
)
result = client.infer_lmm(
    image_path,
    model_id="qwen3_5-2b",
    prompt="Describe this image briefly.",
    max_new_tokens=128,
)
print(result["response"])
```

The code above prints the model response to the terminal:

```
This is a close-up, eye-level shot of a blue beagle dog being carried on the shoulders of a person. The dog has its tongue lolling out in a relaxed, happy expression, looking slightly upward and to the right. Its fur is a vibrant, solid blue with white markings on its chest and muzzle.
```

{% hint style="info" %}
Set `api_url` to match your deployment target:

* `http://localhost:9001` for a local [Inference](https://inference.roboflow.com/) server.
* Your [Dedicated Deployment](/deploy/dedicated-deployments.md) URL for a private endpoint.
  {% endhint %}

You can train your own Qwen3.5 checkpoint on Roboflow and call it by its `workspace/project/version` identifier.

{% embed url="<https://www.youtube.com/watch?v=Y8CR6IzLDaw>" %}


---

# 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.roboflow.com/deploy/supported-models/qwen3-5.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.