Qwen3-VL-32B-Instruct

Qwen3-Open-Source

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Overview

The largest dense model in the Qwen3-VL series, in its non-inference version, delivers overall performance second only to Qwen3-VL-235B-Instruct. It excels in document recognition and comprehension, demonstrates strong spatial awareness and object identification capabilities, and achieves state-of-the-art performance in 2D visual detection and spatial reasoning. It is well-suited for complex perception tasks across a wide range of general-purpose scenarios.

Input

TextImageVideo

Output

Text

Features

Prefix Completion

Function Calling

Cache

Structured Outputs

Batches

Web Search

Pricing

Input
$0.16Per 1M tokens
Output
$0.64Per 1M tokens

Context

131.07K

Max Input

129.02K

Max Output

32.76K

Rate Limits

RPMRequests Per Minute
60
TPMTokens Per Minute
100K

API Reference

Get API Key

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import os
import dashscope
dashscope.base_http_api_url = 'https://dashscope-intl.aliyuncs.com/api/v1'
messages = [
{
    "role": "user",
    "content": [
    {"image": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/ctdzex/biaozhun.jpg"},
    {"text": "Output the text in the image only."}]
}]
response = dashscope.MultiModalConversation.call(
    #If the environment variable is not set, replace it with your Model Studio API key:  api_key ="sk-xxx"
    api_key = os.getenv('DASHSCOPE_API_KEY'),
    model = 'qwen3-vl-32b-instruct',
    messages = messages
)
print(response.output.choices[0].message.content[0]["text"])

import os
import dashscope
dashscope.base_http_api_url = 'https://dashscope-intl.aliyuncs.com/api/v1'
messages = [
{
    "role": "user",
    "content": [
    {"image": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/ctdzex/biaozhun.jpg"},
    {"text": "Output the text in the image only."}]
}]
response = dashscope.MultiModalConversation.call(
    #If the environment variable is not set, replace it with your Model Studio API key:  api_key ="sk-xxx"
    api_key = os.getenv('DASHSCOPE_API_KEY'),
    model = 'qwen3-vl-32b-instruct',
    messages = messages
)
print(response.output.choices[0].message.content[0]["text"])