Qwen2.5 VL AWQ 3B

Qwen2.5 VL AWQ 3B is a vision-language model that supports 3 bilion parameters and offers advanced capabilities such as visual analysis, agentic reasoning, long video comprehension, visual localization, and structured output generation.

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Qwen2.5 VL AWQ 3B is a vision-language model that offers advanced capabilities such as visual analysis, agentic reasoning, long video comprehension, visual localization, and structured output generation. It supports 3 bilion parameters.

Model details

Category	Details
Model Name	Qwen2.5 VL
Version	AWQ 3B
Model Category	VLM
Size	3B params
HuggingFace Model	Qwen/Qwen2.5-VL-3B-Instruct-AWQ
OpenAI Compatible endpoint	Chat API Overview
License	Apache 2.0

Capabilities

Feature	Details
Tool Calling	✅
Context Length	32k tokens
Supports LoRA	✅
Input data	Text + Image

Usage

Basic chat completion

This is a basic chat completion request example using this model:

const modelResponse = await Azion.AI.run("qwen-qwen25-vl-3b-instruct-awq", {

"stream": true,

"messages": [

{

"role": "system",

"content": "You are a helpful assistant."

},

{

"role": "user",

"content": "Name the european capitals"

}

]

})

Property	Type	Description
`stream`	boolean	Indicates whether to stream the response.
`messages[]`	array	Array of message objects, containing the system and user messages.
`messages[].role`	string	The role of the message sender.
`messages[].content`	string	The content of the message.

Response example:

{

"id": "chatcmpl-e27716424abf4b3f891ff4850470cb09",

"object": "chat.completion",

"created": 1746821581,

"model": "qwen-qwen25-vl-3b-instruct-awq",

"choices": [

{

"index": 0,

"message": {

"role": "assistant",

"reasoning_content": null,

"content": "Sure! Here is a list of some European capitals...",

"tool_calls": []

},

"logprobs": null,

"finish_reason": "stop",

"stop_reason": null

}

],

"usage": {

"prompt_tokens": 9,

"total_tokens": 527,

"completion_tokens": 518,

"prompt_tokens_details": null

},

"prompt_logprobs": null

}

Property	Type	Description
`id`	string	Unique identifier for the chat completion.
`object`	string	Type of object.
`created`	number	Timestamp when the chat completion was created.
`model`	string	Model used for chat completion.
`choices[]`	array	Array containing choices made by the model.
`choices[].index`	number	Index of the choice.
`choices[].message`	object	Message returned by the model in the choice.
`choices[].message.role`	string	Role of the message sender.
`choices[].message.reasoning_content`	string	Reasoning behind the model’s response.
`choices[].message.content`	string	Content of message sent by the model.
`choices[].message.tool_calls[]`	array	Array of tool calls.
`choices[].logprobs`	number	Log probabilities.
`choices[].finish_reason`	string	Reason for finishing the response.
`usage`	object	Contains information about token usage.
`usage.prompt_tokens`	number	Number of tokens in the prompt.
`usage.total_tokens`	number	Total number of tokens used.
`usage.completion_tokens`	number	Number of tokens used in the completion.
`usage.prompt_tokens_details`	string	Detailed information about prompt tokens.
`prompt_logprobs`	number	Log probabilities for the prompt.

Tool Calling Example

This is a tool calling request example using this model:

const modelResponse = await Azion.AI.run("qwen-qwen25-vl-3b-instruct-awq", {

"stream": true,

"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"

]

}

]

})

Property	Type	Description
`messages[]`	array	Array containing the messages exchanged between the system and the user.
`messages[].role`	string	The role of the message sender.
`messages[].content`	string	The content of the message.
`tools[]`	array	Array containing the tools used in the query.
`tools[].type`	string	The type of the tool.
`tools[].function`	object	The function being called by the tool.
`tools[].function.name`	string	The name of the function.
`tools[].function.description`	string	A description of the function.
`tools[].function.parameters`	object	The parameters required by the function.

Response example:

{

"id": "chatcmpl-88affc4730cf4219a06d2b15aad9ad44",

"object": "chat.completion",

"created": 1746821866,

"model": "qwen-qwen25-vl-3b-instruct-awq",

"choices": [

{

"index": 0,

"message": {

"role": "assistant",

"reasoning_content": null,

"content": null,

"tool_calls": [

{

"id": "chatcmpl-tool-fd3311e75aed4cbfbeb7244ced77379f",

"type": "function",

"function": {

"name": "get_weather",

"arguments": "{\"location\": \"London\"}"

}

]

},

"logprobs": null,

"finish_reason": "tool_calls",

"stop_reason": null

}

],

"usage": {

"prompt_tokens": 293,

"total_tokens": 313,

"completion_tokens": 20,

"prompt_tokens_details": null

},

"prompt_logprobs": null

}

Property	Type	Description
`choices[]`	array	Array containing the choices made by the assistant.
`choices[].index`	integer	The index of the first choice.
`choices[].message`	object	The message sent by the assistant in the first choice.
`choices[].message.role`	string	The role of the assistant in the message.
`choices[].message.reasoning_content`	null	The reasoning content.
`choices[].message.content`	null	The content of the message.
`choices[].message.tool_calls[]`	array	Array of tool calls invoked by the assistant in the message.
`choices[].message.tool_calls[].id`	string	The ID of the tool call.
`choices[].message.tool_calls[].type`	string	The type of the tool call.
`choices[].message.tool_calls[].function`	object	The function called by the tool.
`choices[].message.tool_calls[].function.name`	string	The name of the function called.
`choices[].message.tool_calls[].function.arguments`	string	The arguments passed to the function in JSON format.
`logprobs`	null	The log probabilities value.
`finish_reason`	string	The reason why the completion finished.
`stop_reason`	null	The reason why the completion was stopped.
`usage.prompt_tokens`	integer	The number of prompt tokens used.
`usage.total_tokens`	integer	The total number of tokens used.
`usage.completion_tokens`	integer	The number of completion tokens used.
`usage.prompt_tokens_details`	null	The details for prompt tokens.
`prompt_logprobs`	null	Log probabilities for the prompt.

Multimodal (text + image) example

This is a multimodal request example using this model:

const modelResponse = await Azion.AI.run("qwen-qwen25-vl-3b-instruct-awq", {

"stream": true,

"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"

}

]

}

]

})

Property	Type	Description
`messages[]`	array	Array containing the messages sent by the system and the user.
`messages[].role`	string	The role of the message sender.
`messages[].content[]`	array	Array containing the content objects in the message.
`messages[].content[]`	object	The content object in the message.
`messages[].content[].type`	string	The type of the content object.
`messages[].content[].image_url`	object	The image URL object in the content object.
`messages[].content[].image_url.url`	string	The URL of the image.
`stream`	boolean	Indicates whether the response should be streamed.

The response will be similar to the one in the basic chat completion example.

JSON schema

{

"$schema": "http://json-schema.org/draft-07/schema#",

"type": "object",

"required": ["messages"],

"properties": {

"messages": {"type": "array", "items": {"$ref": "#/components/schemas/Message"}},

"temperature": {"type": "number", "minimum": 0, "maximum": 2},

"top_p": {"type": "number", "minimum": 0, "maximum": 1, "default": 1},

"n": {"type": "integer", "minimum": 1, "default": 1},

"stream": {"type": "boolean", "default": false},

"max_tokens": {"type": "integer", "minimum": 1},

"presence_penalty": {"type": "number", "minimum": -2, "maximum": 2, "default": 0},

"frequency_penalty": {"type": "number", "minimum": -2, "maximum": 2, "default": 0},

"tools": {"type": "array", "items": {"$ref": "#/components/schemas/ToolDefinition"}}

},

"components": {

"schemas": {

            "Message": {"oneOf": [{"$ref": "#/components/schemas/SystemMessage"},{"$ref": "#/components/schemas/UserMessage"},{"$ref": "#/components/schemas/AssistantMessage"},{"$ref": "#/components/schemas/ToolMessage"}]},

            "SystemMessage": {"type": "object", "required": ["role","content"], "properties": {"role": {"type": "string", "enum": ["system"]}, "content": {"$ref": "#/components/schemas/TextContent"}}},

            "UserMessage": {"type": "object", "required": ["role","content"], "properties": {"role": {"type": "string", "enum": ["user"]}, "content": {"oneOf": [{"type": "string"},{"type": "array", "items": {"oneOf": [{"$ref": "#/components/schemas/TextContentItem"},{"$ref": "#/components/schemas/ImageContentItem"}]}}]}}},

            "AssistantMessage": {"oneOf": [{"$ref": "#/components/schemas/AssistantMessageWithoutToolCalls"},{"$ref": "#/components/schemas/AssistantMessageWithToolCalls"}]},

            "ToolMessage": {"type": "object", "required": ["role","content","tool_call_id"], "properties": {"role": {"enum": ["tool"]}, "content": {"type": "string"}, "tool_call_id": {"type": "string"}}},

            "AssistantMessageWithoutToolCalls": {"type": "object", "required": ["role","content"], "properties": {"role": {"type": "string", "enum": ["assistant"]}, "content": {"$ref": "#/components/schemas/TextContent"}}, "not": {"required": ["tool_calls"]}},

            "AssistantMessageWithToolCalls": {"type": "object", "required": ["role","tool_calls"], "properties": {"role": {"type": "string", "enum": ["assistant"]}, "tool_calls": {"type": "array", "items": {"$ref": "#/components/schemas/ToolCalls"}}}},

            "TextContent": {"oneOf": [{"type": "string"},{"type": "array", "items": {"$ref": "#/components/schemas/TextContentItem"}}], "description": "Text content that can be provided either as a simple string or as an array of TextContentItem objects"},

"ImageContent": {"type": "array", "items": {"$ref": "#/components/schemas/ImageContentItem"}},

            "TextContentItem": {"type": "object", "required": ["type","text"], "properties": {"type": {"type": "string", "enum": ["text"]}, "text": {"type": "string"}}},

            "ImageContentItem": {"type": "object", "required": ["type","image_url"], "properties": {"type": {"type": "string", "enum": ["image_url"]}, "image_url": {"type": "object", "required": ["url"], "properties": {"url": {"type": "string", "format": "uri"}}}}},

            "ToolCalls": {"type": "object", "required": ["function","id","type"], "properties": {"function": {"type": "object", "required": ["name","arguments"], "properties": {"name": {"type": "string"}, "arguments": {"type": "string"}}}, "id": {"type": "string"}, "type": {"enum": ["function"]}}, "description": "The name and arguments of a function that should be called, as generated by the model."},

            "ToolDefinition": {"type": "object", "required": ["type","function"], "properties": {"type": {"type": "string", "enum": ["function"]}, "function": {"type": "object", "required": ["name"], "properties": {"name": {"type": "string"}, "description": {"type": "string"}, "parameters": {"type": "object", "additionalProperties": true}, "strict": {"type": "boolean", "default": false}}}}, "description": "Definition of a tool that can be used by the model"}

}