Qwen3.7-Flash

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Text GenerationVisual UnderstandingReasoning

Overview

Text GenerationVisual UnderstandingReasoning

The Qwen3.7 native vision-language Flash model series delivers a comprehensive upgrade over 3.6-Flash in multimodal understanding and agent execution. This model particularly excels in enhanced multimodal foundations with stronger universal object recognition, further improved real-world perception and spatial intelligence, significantly upgraded multimodal agent capabilities for Search Agent and CI Agent scenarios with more stable end-to-end task execution, as well as optimized multimodal coding for a smoother vibe coding experience.

Input

ImageTextVideo

Output

Text

Features

Prefix Completion

Enable Partial Mode when calling the Qwen API to make the model continue strictly from your provided prefix text.View docs

Function Calling

Use function calling to connect large language models with external tools and systems.View docs

Cache

Context Cache stores shared prefixes for long-context requests to reduce repeated computation, improve latency, and lower cost.View docs

Structured Outputs

Structured Outputs help ensure the model returns a JSON string in the expected format.View docs

Batches

Web Search

Enable web search so the model can answer with real-time retrieved data.View docs

feature.funeTuning

Pricing

Input
$0.03Per 1M tokens
Output
$0.13Per 1M tokens
Input(Implicit Cache)
$0.006Per 1M tokens
Explicit Cache Creation
$0.038Per 1M tokens
Explicit Cache Read
$0.003Per 1M tokens

Input
$0.03Per 1M tokens
Output
$0.13Per 1M tokens
Input(Implicit Cache)
$0.006Per 1M tokens
Explicit Cache Creation
$0.038Per 1M tokens
Explicit Cache Read
$0.003Per 1M tokens

toc.rateLimitsAndContext

Max Input
991.80K
Max Output
65.53K
RPMRequests Per Minute
15K
TPMTokens Per Minute
5M
contextField.maxInputThinking
983.61K
contextField.maxOutputThinking
65.53K
Context
1M

Built-in Tools

code_interpreterResponses API

i2i_searchResponses API

t2i_searchResponses API

web_extractorResponses API

web_searchResponses API

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/20241022/emyrja/dog_and_girl.jpeg"},
            {"text": "What is depicted in the image?"}]
    }]
response = dashscope.MultiModalConversation.call(
    api_key=os.getenv('DASHSCOPE_API_KEY'),
    model='qwen3.7-flash',
    messages=messages
)
print(response.output.choices[0].message.content[0]["text"])