# Qwen2.5 VL AWQ 7B

**Qwen2.5 VL AWQ 7B** is a vision-language model with 7 billion parameters, built for visual analysis, agentic reasoning, long video comprehension, visual localization, and structured output generation. The model accepts text and images in the same request, returns text, and takes tool definitions. [AI Inference](/en/documentation/platform/ai-inference/) runs it under the id `qwen-qwen25-vl-7b-instruct-awq`.

## Model details

These values identify the model. A request names the model id to reach it, and the HuggingFace repository carries the model card.

| Detail                     | Value                                                                                     |
| -------------------------- | ----------------------------------------------------------------------------------------- |
| Model name                 | Qwen2.5 VL                                                                                |
| Version                    | AWQ 7B                                                                                    |
| Model category             | Vision-Language Model (VLM)                                                               |
| Model id                   | `qwen-qwen25-vl-7b-instruct-awq`                                                          |
| Size                       | 7B parameters                                                                             |
| HuggingFace model          | [Qwen/Qwen2.5-VL-7B-Instruct-AWQ](https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct-AWQ) |
| OpenAI-compatible endpoint | [OpenAI Chat API](https://developers.openai.com/api/reference/overview)                   |
| License                    | [Apache 2.0](https://choosealicense.com/licenses/apache-2.0/)                             |

## Capabilities

Qwen2.5 VL AWQ 7B states these capabilities for itself, and none of them is a request field. To read the fields a chat request carries, with their types, defaults, and bounds, refer to [Model invocation](/en/documentation/platform/ai-inference/model-invocation/).

| Capability     | Value          |
| -------------- | -------------- |
| Input data     | Text and image |
| Context length | 32k tokens     |
| Tool calling   | Yes            |
| Supports LoRA  | Yes            |

---

## Usage

Every example on this page calls `Azion.AI.run` from inside a [function](/en/documentation/platform/functions/). The binding takes the model id as its first argument and an OpenAI-compatible request body as its second, so the body never repeats the id. To send the same body to the OpenAI-compatible HTTP endpoint, refer to [Model invocation](/en/documentation/platform/ai-inference/model-invocation/).

### Chat completion

A chat request carries the conversation as a `messages` array, with one system message that sets the behavior and one user message that asks the question:

```ts
const modelResponse = await Azion.AI.run("qwen-qwen25-vl-7b-instruct-awq", {
  "stream": false,
  "messages": [
    { "role": "system", "content": "You are a helpful assistant." },
    { "role": "user", "content": "Name the European capitals." }
  ]
})
```

With `stream` set to `false`, the call resolves to one complete response, and `modelResponse?.choices?.[0]?.message?.content` holds the generated text.

### Tool calling

A tool-calling request keeps the same messages and adds a `tools` array. Every entry declares `type` as `function`, then names the function, describes what it does, and states its `parameters` as a JSON Schema object:

```ts
const modelResponse = await Azion.AI.run("qwen-qwen25-vl-7b-instruct-awq", {
  "stream": false,
  "messages": [
    { "role": "system", "content": "You are a helpful assistant with access to tools." },
    { "role": "user", "content": "What is the weather in London?" }
  ],
  "tools": [
    {
      "type": "function",
      "function": {
        "name": "get_weather",
        "description": "Get the current weather for a location",
        "parameters": {
          "type": "object",
          "properties": {
            "location": {
              "type": "string",
              "description": "The city and state"
            }
          },
          "required": ["location"]
        }
      }
    }
  ]
})
```

A function reads the model's answer from the first entry in `choices` and acts on it, which for this request means calling `get_weather`.

### Multimodal input

A multimodal request puts text and an image in one user message: the `content` field takes an array of parts instead of a string, and each part states its `type`. For the fields each part carries, refer to [Model invocation](/en/documentation/platform/ai-inference/model-invocation/). This request sends a question and an image URL together:

```ts
const modelResponse = await Azion.AI.run("qwen-qwen25-vl-7b-instruct-awq", {
  "stream": false,
  "messages": [
    { "role": "system", "content": "You are a helpful assistant." },
    {
      "role": "user",
      "content": [
        { "type": "text", "text": "What is in this image?" },
        { "type": "image_url", "image_url": { "url": "https://example.com/image.jpg" } }
      ]
    }
  ]
})
```

The model reads the image from the URL the request gives it, and answers in text at `modelResponse?.choices?.[0]?.message?.content`.

---

## Related resources

- [Model invocation](/en/documentation/platform/ai-inference/model-invocation.md): How a request reaches a model, through the binding or over HTTP, and what its body carries.
- [AI models](/en/documentation/platform/ai-inference/models.md): The rest of the catalog, with the capabilities each model states for itself.
- [AI Inference](/en/documentation/platform/ai-inference.md): What AI Inference is, and what it does with a model request.
- [Functions](/en/documentation/platform/functions.md): Where the code on this page runs, and how you deploy it.
- [LoRA Fine-Tune](/en/documentation/platform/ai-inference/lora-fine-tune.md): The extension of AI Inference that adapts a model with LoRA, and the models that accept it.
- [Glossary](/en/documentation/platform/ai-inference/glossary.md): The AI Inference terms this page uses, defined in one place.