FlagshipAlibaba

Qwen VL Max

Qwen VL Max is Alibaba's flagship multimodal model supporting text and image inputs with a 131K token context window for vision-language tasks.

Context 131K
Tier Flagship
Modalities text, image
Input from
$0.520 / 1M tokens
across 1 provider

API Pricing

ProviderInput / 1MOutput / 1MUpdated
$0.520$2.084/14/2026

Prices updated daily. Last check: 4/14/2026

Model Details

General

Creator
Alibaba
Family
Qwen
Tier
Flagship
Context Window
131K
Modalities
Text, Image

Capabilities

Tool Calling
No
Open Source
No

Strengths & Limitations

  • Multimodal processing supporting both text and image inputs
  • Large 131K token context window for extended conversations
  • Flagship-tier capabilities from Alibaba's model family
  • Designed for vision-language understanding tasks
  • Can process multiple images within the extended context
  • Suitable for document analysis with visual elements
  • Strong foundation in Chinese language processing given Alibaba's background
  • No function calling or tool use capabilities
  • Proprietary model with no open-source weights available
  • Limited to text and image modalities only
  • Smaller context window compared to some contemporary flagship models
  • No video or audio input support

Key Features

131,072 token context window
Multimodal text and image processing
Vision-language understanding
Image analysis and interpretation
Visual question answering
Document processing with images
Multimodal reasoning capabilities
Extended context for multiple images

About Qwen VL Max

Qwen VL Max is Alibaba's flagship multimodal model in the Qwen family, designed to handle both text and image inputs simultaneously. As a proprietary model from one of China's leading technology companies, it represents Alibaba's most capable offering for vision-language understanding tasks. The model features a 131,072 token context window and processes both text and image modalities, enabling it to analyze visual content, answer questions about images, and perform multimodal reasoning tasks. Unlike some models in the Qwen family, Qwen VL Max does not support function calling, focusing instead on core vision-language capabilities. Qwen VL Max is positioned for applications requiring sophisticated visual understanding combined with text processing, such as document analysis, image captioning, visual question answering, and multimodal content generation. Its large context window allows for processing lengthy documents with embedded images or multiple images within a single conversation.

Common Use Cases

Qwen VL Max is well-suited for multimodal applications that require processing both text and visual content simultaneously. Its flagship-tier capabilities make it appropriate for complex vision-language tasks such as analyzing documents with charts and diagrams, generating detailed image descriptions, answering questions about visual content, and performing multimodal reasoning across text and images. The extended context window enables processing multiple images in a single session or analyzing lengthy documents with embedded visual elements, making it valuable for research, content analysis, educational applications, and business document processing where visual understanding is critical.

Frequently Asked Questions

How much does Qwen VL Max cost per million tokens?

Qwen VL Max pricing varies by provider and may include different rates for text and image tokens. Check the pricing table above for current rates across all available providers.

What is Qwen VL Max best used for?

Qwen VL Max excels at multimodal tasks requiring both text and image understanding, including visual question answering, document analysis with charts or diagrams, image captioning, and multimodal reasoning. Its large context window makes it particularly suitable for processing multiple images or lengthy documents with visual elements.

Does Qwen VL Max support function calling or tool use?

No, Qwen VL Max does not support function calling or tool use capabilities. It focuses on core vision-language understanding tasks, processing text and image inputs for analysis, reasoning, and generation without external tool integration.