---
title: MJev-Spatial
emoji: 🧭
colorFrom: yellow
colorTo: blue
sdk: gradio
sdk_version: 6.30.0
app_file: app.py
short_description: Spatial VLM that decides in one forward pass
python_version: "3.12"
startup_duration_timeout: 30m
---

# MJev-Spatial

Demo of **MJev-Spatial: System One Spatial Intelligence via Native Attention Matching**
([arXiv 2610.22276](https://arxiv.org/abs/2610.22276) · [GitHub](https://github.com/Fr0zenCrane/MJev-Spatial)).

MJev-Spatial is a 4B multimodal decision model built on Qwen3.5-4B. It turns a spatial
question into a finite candidate-selection problem and scores those candidates in a
**single forward pass** with no generated answer tokens, reusing the language backbone's
final full-attention layer's native query/key projections as the readout.

The demo exposes the three answer spaces from the paper:

- **Choice** — pick one of the supplied options (e.g. relative-direction questions).
- **Scalar** — estimate a nonnegative measurement in meters via an interval hierarchy.
- **Pointing** — point at a requested target in the image; the predicted point is
  drawn on the image (the model makes three 3×3 region decisions, refining a crop).

Example image: `examples/images/scene.png` from the official
[MJev-Spatial repository](https://github.com/Fr0zenCrane/MJev-Spatial) (Apache-2.0).