LightweightAlibaba

Qwen VL Plus

Qwen VL Plus is Alibaba's lightweight multimodal model that processes text and images with a 131K token context window.

Context 131K
Tier Lightweight
Modalities text, image
Input from
$0.137 / 1M tokens
across 1 provider

API Pricing

ProviderInput / 1MOutput / 1MSpeedTTFTUpdated
$0.137$0.40951.8 t/s1.3s4/14/2026

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

Model Details

General

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

Capabilities

Tool Calling
No
Open Source
No

Strengths & Limitations

  • Multimodal support for both text and image inputs
  • 131K token context window for processing lengthy multimodal content
  • Fast inference speed at 51.75 tokens per second
  • Lightweight architecture optimized for efficiency
  • Reasonable time-to-first-token at 1.3 seconds
  • Created by Alibaba with focus on practical multimodal applications
  • No tool calling or function execution capabilities
  • Proprietary model with weights not publicly available
  • Lightweight tier limits complex reasoning compared to flagship models
  • Limited to text and image modalities only

Key Features

131,072 token context window
Text and image input processing
Multimodal content understanding
Streaming response generation
Fast inference optimization
Vision-language integration
Batch processing support

About Qwen VL Plus

Qwen VL Plus is Alibaba's lightweight multimodal model within the Qwen family, designed for efficient text and image processing tasks. As a lightweight tier model, it balances capability with performance, offering faster inference speeds compared to larger models in the family. The model supports both text and image inputs with a 131,072 token context window, allowing it to process substantial amounts of multimodal content in a single request. Performance benchmarks show it generates approximately 52 tokens per second with a time-to-first-token of 1.3 seconds. The model does not include tool calling capabilities, focusing instead on core multimodal understanding and generation. Qwen VL Plus serves applications requiring efficient multimodal processing where speed and cost-effectiveness are priorities over maximum capability. It competes with other lightweight multimodal models by providing solid vision-language performance while maintaining faster inference speeds suitable for production deployments.

Common Use Cases

Qwen VL Plus is well-suited for applications requiring efficient multimodal processing at scale, such as content moderation with both text and images, document analysis combining visual and textual elements, automated image captioning, and customer service chatbots that need to understand uploaded images. Its lightweight design makes it appropriate for high-volume deployments where processing speed and cost efficiency are important, such as e-commerce product description generation, social media content analysis, or educational platforms processing mixed media content. The model's balance of multimodal capability and performance optimization makes it ideal for production environments that need reliable vision-language understanding without the overhead of larger flagship models.

Frequently Asked Questions

How much does Qwen VL Plus cost per million tokens?

Qwen VL Plus pricing varies by provider and pricing type (standard vs batch). Check the pricing table above for current rates across all providers.

What is Qwen VL Plus best used for?

Qwen VL Plus excels at multimodal tasks requiring efficient processing of text and images, such as content moderation, document analysis, image captioning, and customer service applications. Its lightweight design makes it ideal for high-volume production deployments where speed and cost-effectiveness are priorities.

Does Qwen VL Plus support tool calling or function execution?

No, Qwen VL Plus does not include tool calling capabilities. It focuses on core multimodal understanding and generation tasks with text and image inputs, making it more suitable for direct content processing rather than agentic workflows that require external tool integration.