# Qwen 3.8 Max Live Now

> Source: <https://www.qwencloud.com/models/qwen3.8-max>
> Published: 2026-08-03 02:18:40+00:00

### Qwen3.8-Max

Copied!

[Try AI](https://www.qwencloud.com/try-ai/chat?models=qwen3.8-max)

[Add to Compare](/compare?models=qwen3.8-max)

ReasoningVisual UnderstandingText Generation

## Overview

ReasoningVisual UnderstandingText Generation

2.4-trillion-parameter MoE flagship delivering a comprehensive leap in coding and professional work. Autonomously codes and delivers complete projects spanning 10+ days. Handles hundreds of specialized tasks across legal, financial, design, and other professional domains, producing production-grade results end-to-end in a single conversation. Native visual understanding runs through the full cycle of planning, execution, and verification, enabling deep semantic analysis of ultra-long documents and extended video content. In long-horizon tasks, plans autonomously, iterates through closed feedback loops, and continuously evolves.

#### 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](https://docs.qwencloud.com/developer-guides/text-generation/partial-mode)

#### Function Calling

Use function calling to connect large language models with external tools and systems.[View docs](https://docs.qwencloud.com/developer-guides/text-generation/function-calling)

#### Cache

Context Cache stores shared prefixes for long-context requests to reduce repeated computation, improve latency, and lower cost.[View docs](https://docs.qwencloud.com/developer-guides/text-generation/context-cache#implicit-cache)

#### Structured Outputs

Structured Outputs help ensure the model returns a JSON string in the expected format.[View docs](https://docs.qwencloud.com/developer-guides/text-generation/structured-output)

#### Batches

#### feature.funeTuning

## Pricing

- Input$2Per 1M tokens
- Output$6Per 1M tokens
- Input(Implicit Cache)$0.25Per 1M tokens
- Explicit Cache Creation$2.5Per 1M tokens
- Explicit Cache Read$0.17Per 1M tokens

## Rate Limits & Context

- Max Input991.80K
- Max Output131.07K
- RPMRequests Per Minute15K
- TPMTokens Per Minute2M
- Max Input (Thinking)983.61K
- Max Output (Thinking)131.07K
- Context1M

## Built-in Tools

[code_interpreter](https://docs.qwencloud.com/developer-guides/text-generation/code-interpreter)Responses API

[web_extractor](https://docs.qwencloud.com/developer-guides/text-generation/web-scraping)Responses API

[web_search](https://docs.qwencloud.com/developer-guides/text-generation/web-search)Responses API

[t2i_search](https://docs.qwencloud.com/developer-guides/text-generation/image-search)Responses API

[i2i_search](https://docs.qwencloud.com/developer-guides/text-generation/image-search)Responses API

## API Reference

[Get API Key](https://home.qwencloud.com/api-keys)

Copied!

123456789101112131415161718

``` python
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='qwen3.8-max',
    messages=messages
)
print(response.output.choices[0].message.content[0]["text"])
```