Qwen-Image-2.1 Description

Qwen-Image-2.1 is an advanced model for text-to-image creation and image modification, part of the Qwen series, engineered to effectively balance the quality of generated images, the efficiency of inference, and overall adaptability. With a visual generation architecture comprising 7 billion parameters and utilizing 32 Single-Stream DiT layers, it features a streamlined design that integrates mixed-granularity attention alongside prefix KV cache reuse, enabling high-quality image outputs while minimizing computational demands. This model offers native capabilities for creating both standard and transparent RGBA images, facilitating transparent-layer editing and allowing for subject extraction from images, all integrated within a single framework. For editing purposes, it accommodates up to ten reference images for complex multi-subject arrangements, takes local editing commands via circles, painted notes, or distinct masks, and maintains the integrity of individuals and products throughout the process. Enhancements in typography, portrait illumination, realistic textures, and intricate details have been implemented to yield results that are not only more polished but also visually striking. Additionally, this model’s versatility in handling various image generation tasks sets it apart in the realm of image synthesis technology.

Integrations

API:
Yes, Qwen-Image-2.1 has an API

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Company Details

Company:
Alibaba
Year Founded:
1999
Headquarters:
China
Website:
github.com/QwenLM/Qwen-Image-2.1

Media

Qwen-Image-2.1 Screenshot 1
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Product Details

Platforms
Web-Based
Types of Training
Training Docs
Customer Support
Online Support

Qwen-Image-2.1 Features and Options

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