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LatestQwen · Alibaba2.1
Qwen · AlibabaText → Image

Qwen-Image-2.1 Adds RGBA to Image Generation

Alibaba's Qwen team updates its open image model with transparency support and joint text-to-image and editing capabilities.

Sep 14, 2026
NotableOther
Qwen-Image-2.1

Alibaba's Qwen team has published Qwen-Image-2.1 on Hugging Face, an image model that handles both text-to-image generation and image editing in a single package. The headline addition this time is RGBA support, meaning the model can produce images with a genuine alpha channel rather than flat, opaque frames.

That transparency capability is more consequential than it sounds. Most open image generators output solid backgrounds, forcing designers to run a separate cutout or masking step. Native RGBA lets the model emit assets — logos, icons, product shots, UI elements — that drop cleanly onto other layers.

Why it matters

Qwen has been steadily building out an open multimodal stack, and combining generation with editing in one model lowers the barrier for developers who want a single dependency rather than a pipeline of specialized tools. Key points from the release:

  • Covers both text-to-image and image editing workflows
  • Adds RGBA / transparency output
  • Distributed openly through Hugging Face under a custom license

As always with open weights, the practical details — resolution ceilings, hardware requirements, and the exact license terms — are worth checking on the model card before building it into production. But the direction is clear: Qwen is positioning its image model as a self-contained creative tool rather than a raw research artifact.

Sources

  • Qwen/Qwen-Image-2.1

    Hugging Face

    Visit
OlderYandex releases 80B MoE base model under Apache 2.0Yandex · Text / LLM · 2 months agoNewerEmbeddingGemma 2 Expands to Any ModalityGoogle DeepMind · Embeddings · 2 months ago

Get the model

Hugging Face

Specs

Size14.2 GB
PrecisionBF16
ArchitectureQwenImage21Pipeline
LicenseOTHER
Downloads253.2K
Likes3.6K

Can you run it?

Runs on a laptop — about 8.1 GB at FP8.

  • BF16 (as published)

    16 GB GPU (RTX 4080 / 5070 Ti) · 24 GB Mac

    15.2 GB
  • FP8

    12 GB GPU (RTX 3060 / 4070) · 16 GB Mac

    8.1 GB
Your machine
  • Covers the published checkpoint; text encoders and VAE loaded alongside may add a few GB (many runtimes offload them to CPU).

Based on Hugging Face weights metadata. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

Text → ImageImage Editing

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