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license: apache-2.0
language:
- en
base_model:
- Qwen/Qwen3.5-35B-A3B
pipeline_tag: image-text-to-text
library_name: transformers
tags:
- multimodal
- action
- agent
- pytorch
- computer use
- gui agents
- moe
---
# **Holo3: Foundational Models for Navigation and Computer Use Agents**
## **Model Description**
**Holo3** is our latest generation of large-scale Vision-Language Models (VLMs) specifically optimized for **GUI Agents**. Like its predecessors, it operates across diverse digital environments—web, desktop, and mobile—by interpreting visual interfaces, reasoning over complex content, and executing precise actions.
Holo3 achieves **state-of-the-art performance on OSWorld-Verified**, setting a new benchmark for computer use agents. While it retains the world-class web navigation capabilities of **Holo2**, the new **Holo3-35B-A3B** architecture is designed to thrive in realistic business environments.
* **Developed by:** [**H Company**](https://www.hcompany.ai/)
* **Model type:** Vision-Language Model for Navigation and Computer Use Agents
* **Architecture:** Sparse Mixture-of-Experts (MoE) with 35B total / 3B active parameters
* **Fine-tuned from model:** Qwen/Qwen3.5-35B-A3B
* **Blog Post:** [hcompany.ai/holo3](https://www.hcompany.ai/holo3)
* **Quickstart:** [hub.hcompany.ai/quickstart](https://hub.hcompany.ai/quickstart)
* **License:** Apache 2.0 License
---
<div align="center">
<p align="center"><img width=800 src="osworld_pareto_light.png"/></p>
</div>
---
## **Get Started**
Explore our [Quickstart guide](https://hub.hcompany.ai/quickstart) to learn how to integrate with our inference API.
---
## **Training Strategy**
**Holo3-35B-A3B** is based on the **Qwen3.5** architecture and has been reinforced to strengthen its core agentic pillars: perception and decision-making. The training pipeline utilizes a carefully curated mix of open-source datasets, large-scale synthetic trajectories, and high-quality human-annotated samples to ensure reliable multi-step reasoning.
---
## **Results**
### **State-of-the-Art Navigation (OSWorld-Verified)**
To benchmark **Holo3** on computer use and web navigation, we utilized the OSWorld and WebArena benchmarks. **Holo3-35B-A3B** achieves a **77.8%** score on OSWorld-Verified. Remarkably, it achieves this with only **3B active parameters**, providing SOTA performance at a fraction of the inference cost of leading proprietary models.
### **Enterprise Readiness (H Corporate Benchmark)**
To measure real-world utility, we developed the **H Corporate Benchmark**: a dedicated evaluation suite of 486 multi-step tasks across four categories: E-commerce, Business Software, Collaboration, and Multi-App workflows. Holo3 consistently outperforms significantly larger competitors in these dense, business-logic environments.
### **UI Localization & Grounding**
A world-class agent must see before it can act. Holo3 excels at localizing interaction elements and understanding their functions, as evidenced by top-tier performance on **ScreenSpot-Pro** and **OSWorld-G**.
<div align="center">
**Table 1: Evaluation results on computer use and grounding benchmarks.**
<p align="center"><img width=800 src="benchmark_table_light.png"/></p>
</div>
---
## **Citation**
```bibtex
@misc{hai2025holo3modelfamily,
title={Holo3 - Open Foundation Models for Navigation and Computer Use Agents},
author={H Company},
year={2026},
url={https://huggingface.co/Hcompany/Holo3-35B-A3B},
}
```
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