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LatestSkyworkUniPic-1.5B
SkyworkAny-to-Any

Skywork Releases UniPic, a Unified 1.5B Vision Model

The new autoregressive model from the Chinese AI lab can understand, generate, and edit images within a single, compact framework.

Jul 29, 2025
UpdateOther
Skywork-UniPic-1.5B

AI lab Skywork, known for its Chinese-language LLMs, has released Skywork-UniPic-1.5B, a compact multimodal model designed to handle a variety of vision tasks within a single architecture. At just 1.5 billion parameters, UniPic uses a unified autoregressive approach to process and create images, a departure from more specialized, single-task models.

The key feature of UniPic is its versatility. Instead of requiring separate models for different functions, it integrates several core capabilities into one system. This multi-task design represents a growing trend towards more efficient and generalized AI systems that can reason about and manipulate visual data more holistically.

A Unified Vision Framework

UniPic is capable of performing three primary functions:

  • Image Understanding: The model can interpret the content of an image and answer questions about it.
  • Image Generation: It can create new images from descriptive text prompts.
  • Image Editing: It can modify existing images based on user instructions.

The model, code, and further details are available on the project's Hugging Face repository. It is released under the Skywork License Agreement, which allows for research and commercial use with certain restrictions. Its relatively small size could make it an accessible tool for researchers and developers experimenting with unified vision architectures.

Sources

  • Skywork/Skywork-UniPic-1.5B

    Hugging Face

    Visit
OlderAlibaba Releases Wan2.2, a 14B MoE Video ModelQwen · Alibaba · Image → Video · last yearNewerNew VLM `dots.ocr` Takes on Complex Documentsrednote-hilab · Vision-Language · last year

Get the model

Hugging Face

Specs

Parameters1.5B
LicenseOTHER
Downloads68
Likes115

Can you run it?

Runs on just about anything.

  • BF16 (as published)

    8 GB GPU (RTX 4060) · 16 GB laptop or Mac

    4.5 GB
  • 8-bit

    Any modern laptop · 8 GB RAM

    3.1 GB
  • 4-bit

    Any modern laptop · 8 GB RAM

    2.4 GB
Your machine
  • Precision not published; assuming 16-bit (BF16) weights.
  • Parameter count is an editorial estimate — no weights metadata on Hugging Face.
  • KV cache approximated from model size (no config metadata) at 8,192 tokens.

Estimated from the parameter count. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

Any-to-AnyText → ImageImage Editing

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