Multimodal benchmark

# SpatialViz-Bench leaderboard

> SpatialViz-Bench results for 8 AI models, led by Gemini 2.5 Pro at 44.7%. What the benchmark measures, who runs it, and a source for every score.
- Canonical page: https://noometry.com/benchmarks/spatialviz-bench
- Last updated: 2026-10-10
- Title: SpatialViz-Bench Leaderboard (October 2026): Scores by Model

As of October 2026, Gemini 2.5 Pro has the highest published SpatialViz-Bench score on Noometry at 44.7%, out of 8 models with results.

Last verified October 10, 2026

## About SpatialViz-Bench

Spatial visualization tasks such as mental rotation and paper folding.

- **Category:** [Multimodal](https://noometry.com/best/multimodal)
- **Introduced:** 2025
- **Unit:** Percent (random guessing ≈ 0%)
- **Official site:** [github.com](https://github.com/wangst0181/Spatial-Visualization-Benchmark)

## Top 8 models

Top models on SpatialViz-Bench

1.  Gemini 2.5 Pro 44.7%
2.  o1 41.4%
3.  Gemini 2.5 Flash 36.9%
4.  Llama 4 Scout 34.2%
5.  Claude 3.7 Sonnet 33.9%
6.  Qwen2.5-VL 72B Instruct 33.3%
7.  Qwen-VL Max 32%
8.  Llama 4 Maverick 31.8%
9.  2530354045

Sponsored placements are available on pages like this one. [Advertise on Noometry](https://noometry.com/advertise)

## All results

SpatialViz-Bench results by model
| # | Model | Provider | Score | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- | --- |
| 1 | [Gemini 2.5 Pro](https://noometry.com/models/gemini-2-5-pro) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 44.7% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 2 | [o1](https://noometry.com/models/o1) | [OpenAI](https://noometry.com/providers/openai) | 41.4% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 3 | [Gemini 2.5 Flash](https://noometry.com/models/gemini-2-5-flash) |  [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 36.9% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 4 | [Llama 4 Scout](https://noometry.com/models/llama-4-scout) |  [![](/logos/meta.svg) Meta](https://noometry.com/providers/meta) | 34.2% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 5 | [Claude 3.7 Sonnet](https://noometry.com/models/claude-3-7-sonnet) | [Anthropic](https://noometry.com/providers/anthropic) | 33.9% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 6 | [Qwen2.5-VL 72B Instruct](https://noometry.com/models/qwen2-5-vl-72b-instruct) |  [![](/logos/alibaba.svg) Alibaba (Qwen)](https://noometry.com/providers/alibaba) | 33.3% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 7 | [Qwen-VL Max](https://noometry.com/models/qwen-vl-max) |  [![](/logos/alibaba.svg) Alibaba (Qwen)](https://noometry.com/providers/alibaba) | 32% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| 8 | [Llama 4 Maverick](https://noometry.com/models/llama-4-maverick) |  [![](/logos/meta.svg) Meta](https://noometry.com/providers/meta) | 31.8% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |

## Compare the leaders

-   [Gemini 2.5 Pro vs o1](https://noometry.com/compare/gemini-2-5-pro-vs-o1)
-   [Gemini 2.5 Pro vs Gemini 2.5 Flash](https://noometry.com/compare/gemini-2-5-flash-vs-gemini-2-5-pro)
-   [Gemini 2.5 Pro vs Llama 4 Scout](https://noometry.com/compare/gemini-2-5-pro-vs-llama-4-scout)
-   [Gemini 2.5 Pro vs Claude 3.7 Sonnet](https://noometry.com/compare/claude-3-7-sonnet-vs-gemini-2-5-pro)
-   [o1 vs Gemini 2.5 Flash](https://noometry.com/compare/gemini-2-5-flash-vs-o1)
-   [o1 vs Llama 4 Scout](https://noometry.com/compare/llama-4-scout-vs-o1)

## Other multimodal benchmarks

-   [LMArena Vision](https://noometry.com/benchmarks/arena-vision)
-   [Video-MME](https://noometry.com/benchmarks/video-mme)
-   [GeoBench](https://noometry.com/benchmarks/geobench)
-   [VPCT](https://noometry.com/benchmarks/vpct)
-   [Blueprint-Bench 2](https://noometry.com/benchmarks/blueprint-bench-2)
-   [Furniture Assembly](https://noometry.com/benchmarks/furniture-assembly)
-   [LMArena Document](https://noometry.com/benchmarks/arena-document) (reference)
-   [MindCube](https://noometry.com/benchmarks/mindcube) (reference)
-   [ScienceQA](https://noometry.com/benchmarks/scienceqa) (reference)

## Frequently asked questions

### What does SpatialViz-Bench measure?

Spatial visualization tasks such as mental rotation and paper folding.

### Which model has the highest SpatialViz-Bench score?

As of October 2026, Gemini 2.5 Pro has the highest published SpatialViz-Bench score on Noometry at 44.7%, out of 8 models with results.

### What is the best open-weight model on SpatialViz-Bench?

Llama 4 Scout has the highest SpatialViz-Bench accuracy among open-weight models at 34.2%, ranking 4 of 8 overall.

### Cite this page

Noometry. (2026). SpatialViz-Bench leaderboard. Retrieved October 10, 2026, from https://noometry.com/benchmarks/spatialviz-bench

Quote Noometry with a link back to this page. It is also available in [Markdown](https://noometry.com/md/benchmarks/spatialviz-bench.md).