Qwen Image 2.1: Unified Image Generation and Editing

Qwen Image 2.1 is a unified text-to-image generation and image editing model in the Qwen series. Where earlier releases split generation and editing across Qwen Image and Qwen Image Edit, version 2.1 handles both in a single model. Its visual generation component has just 7B parameters across 32 single-stream DiT layers, so it produces high-quality images at a fraction of the compute of larger diffusion models.

Compact and Efficient Architecture

The model uses mixed-granularity attention and prefix KV cache reuse to keep inference cheap without sacrificing output quality. It generates at a native 2048 x 2048 resolution, with supported aspect ratios from 1:1 through 16:9 and 9:16, including 4:3, 3:4, 3:2, and 2:3 formats.

Native Transparency

Qwen Image 2.1 generates transparent RGBA images directly from text prompts, so there is no separate background-removal pass. The same model can edit transparent layers and extract subjects from ordinary photographs, turning a product shot or portrait into a clean cutout ready for compositing. Stickers, icons, logos, and design assets come out with a real alpha channel.

Versatile Editing

Editing accepts up to 10 reference images in a single request. You can mark local edits by drawing circles, painting annotations, or providing a separate mask, and the model preserves identity for both people and products across edits. This makes it possible to combine several individually photographed portraits into one coherent group shot, or to place a product into a new scene without it drifting from the original.

Realistic Textures and Refined Aesthetics

The release improves typography, portrait lighting, and fine surface detail. Text rendering carries over the Qwen series' strength with legible, well-composed lettering, which is useful for signage, posters, and product packaging.

Use Cases

• Transparent assets for design systems, stickers, icons, and UI graphics
• Subject extraction and background removal from photographs
• Product photography variants with consistent product identity
• Multi-reference composition, such as group photos assembled from individual portraits
• Localized edits guided by masks or painted annotations
• Posters, signage, and marketing graphics with accurate in-image text

Included ComfyUI Workflows

This template ships with three ready-to-run ComfyUI workflows: text-to-image generation, reference-based image editing, and background removal. They use the Comfy-Org INT8 repackage of the diffusion model and the Qwen3-VL 8B text encoder, which keeps memory use low while preserving quality. For the earlier generation of the family, see the Qwen Image and Qwen Image Edit entries.