---
title: "Show-o"
description: "Show-o from National University of Singapore (Show Lab): multimodal-generation and text-to-image; Verified."
modelId: "show-o"
pageSource: generated
---

Show-o (Xie et al., Show Lab at NUS with ByteDance, arXiv 2408.12528) is a single 1.3B transformer that unifies multimodal understanding and generation. It is initialized from Phi-1.5 and, unlike systems that attach a separate diffusion expert to an MLLM, uses one set of weights for both.

<ModelPaperFigures modelId="show-o" locale="en" />

The recorded paper is [Show-o: One Single Transformer to Unify Multimodal Understanding and Generation](https://arxiv.org/abs/2408.12528) (ICLR 2025, 2024).

Project page: [showlab.github.io/Show-o](https://showlab.github.io/Show-o/). Code: [showlab/Show-o](https://github.com/showlab/Show-o).

<ModelCommandBuilder modelId="show-o" locale="en" />

## What it is for

Use `show-o` when the job is a catalog still image rather than video.

Image I/O uses the MAGVIT-v2 VQ tokenizer (showlab/magvitv2). The paper also studies continuous MAGVIT or CLIP-ViT features for understanding (Show-o† / Show-o‡); the released default and these catalog weights use discrete tokens for both understanding and generation. WorldFoundry's runtime lives under synthesis/visual_generation/show_o with a mode/prompt/image contract and microsoft/phi-1_5 plus showlab/show-o. It is published by National University of Singapore (Show Lab).

Catalog tasks include multimodal-generation and text-to-image. Catalog aliases include `show_o` and `showo`. Documented modalities: text and image in, image and text out.

## Runtime contract

Optional `prompt`, `input_path`, `interactions`, `fps`, and `guidance_scale`; artifacts `show_o.png`.

CLI task profiles: `default`. WorldFoundry binds `ShowOPipeline`.

Family status: **Verified**.

The verified WorldFoundry route is T2I only — set mode accordingly and expect a generated_image artifact. Paper-default resolution is 256; the wrapper uses classifier-free guidance (default 3.0) and 18 discrete-diffusion steps. Weights are MIT at showlab/show-o, with MAGVIT-v2 and Phi-1.5 as recorded companions. Image understanding and editing modes exist in the paper but are not wired here.

Runtime source is vendored in-tree; current WorldFoundry wrapper supports t2i image generation.

## Running in WorldFoundry

The catalog launch is `worldfoundry-eval run show-o --pipeline.task-profile default`. The command builder above switches `--pipeline.task-profile` among recorded tasks and still emits `worldfoundry-eval run`.

It runs in the unified environment `worldfoundry-unified-cu128` (Python 3.11, CUDA 11.3).

Recorded weight repositories include `showlab/show-o`, `showlab/magvitv2`, and `microsoft/phi-1_5`. Prepare the environment and check local assets with `bash scripts/inference/prepare_model_infer.sh show-o`. Add `--download` to fetch missing public checkpoints.

Recorded licenses include mit; status: **Verified**.

<ModelRelatedRecipes modelId="show-o" locale="en" />