---
title: "SpatialLadder"
description: "SpatialLadder: multimodal-reasoning and spatial-reasoning; Runner parity pending."
modelId: "spatial-ladder"
pageSource: generated
---

SpatialLadder is a 3B multimodal model specialized in spatial reasoning — answering questions about spatial relations in images and videos. The catalog records it for multimodal/spatial reasoning and image/video QA with model_response artifacts; weights live at hongxingli/SpatialLadder-3B.

<ModelPaperFigures modelId="spatial-ladder" locale="en" />

Code: [hongxingli/SpatialLadder-3B](https://huggingface.co/hongxingli/SpatialLadder-3B).

<ModelCommandBuilder modelId="spatial-ladder" locale="en" />

## What it is for

Use `spatial-ladder` for multimodal reasoning inference on this card.

A 3B-parameter vision-language model; the staged-training design implied by its name (progressive spatial reasoning) is described upstream, and the publishing institution and internals are not recorded in this repository.

Catalog tasks include multimodal-reasoning, spatial-reasoning, image-question-answering, and video-question-answering. Catalog aliases include `spatial_ladder` and `hongxingli/SpatialLadder-3B`.

## Runtime contract

Optional `prompt`, `image`, `video`, `seed`, and `frames`; artifacts `spatial-ladder.json`.

CLI task profiles: `multimodal-reasoning`, `spatial-reasoning`, `image-question-answering`, `video-question-answering`, and `video_generation`. WorldFoundry binds `SpatialLadderPipeline`.

Family status: **Runner parity pending**.

Use it as a lightweight spatial-QA judge for generated scenes; the 3B scale runs on modest GPUs.

WorldFoundry route is complete; missing checkpoint/assets are reported at runtime.

## Running in WorldFoundry

The catalog launch is `worldfoundry-eval run spatial-ladder --pipeline.task-profile multimodal-reasoning`. 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 12.8).

Recorded weight repositories include `hongxingli/SpatialLadder-3B`. Prepare the environment and check local assets with `bash scripts/inference/prepare_model_infer.sh spatial-ladder`. Add `--download` to fetch missing public checkpoints.

Status: **Runner parity pending**.

<ModelRelatedRecipes modelId="spatial-ladder" locale="en" />