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README.md
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---
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tags:
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- multimodal
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- NPU
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- On-device
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- Snapdragon PC
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- Android
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license: other
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license_name: nexa-research
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license_link: LICENSE
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---
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<p align="center">
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<img alt="omnineural" src="https://cdn-uploads.huggingface.co/production/uploads/6618e0424dbef6bd3c72f89a/zRUnoWmw43fl9hrXHg0pE.png">
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</p>
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# **OmniNeural** — World’s First NPU-aware Multimodal Model
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## **Overview**
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**OmniNeural** is the first fully multimodal model designed specifically for Neural Processing Units (NPUs). It natively understands **text, images, and audio**, and runs across PCs, mobile devices, automobile, IoT, and robotics.
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## Demos
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### 📱 Mobile Phone NPU - Demo on Samsung S25 Ultra
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The first-ever fully local, multimodal, and conversational AI assistant that hears you and sees what you see, running **natively on Snapdragon NPU** for long battery life and low latency.
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<video controls width="720" preload="metadata"
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src="https://huggingface.co/NexaAI/OmniNeural-4B/resolve/main/assets/MOBILE_50MB.mp4"
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type="video/mp4"></video>
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---
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## ✨ PC NPU - Capabilities Highlights
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<table>
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<tr>
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<td width="33%">
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<video controls width="100%" preload="metadata"
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src="https://huggingface.co/NexaAI/OmniNeural-4B/resolve/main/assets/PC_demo_2_image.mov"></video>
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<p align="center"><b>🖼️ Multi-Image Reasoning</b><br>Spot the difference across two images in multi-round dialogue.</p>
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</td>
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<td width="33%">
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<video controls width="100%" preload="metadata"
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src="https://huggingface.co/NexaAI/OmniNeural-4B/resolve/main/assets/PC_Demo_Agent.mov"></video>
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<p align="center"><b>🤖 Image + Text → Function Call</b><br>Snap a poster, add a text instruction, and AI agent creates a calendar event.</p>
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</td>
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<td width="33%">
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<video controls width="100%" preload="metadata"
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src="https://huggingface.co/NexaAI/OmniNeural-4B/resolve/main/assets/PC_Demo_Audio.mov"></video>
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<p align="center"><b>🎶 Multi-Audio Comparison</b><br>Tell the difference between two music clips locally.</p>
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</td>
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</tr>
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</table>
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---
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## **Key Features**
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- **Multimodal Intelligence** – Processes **text, image, and audio** in a unified model for richer reasoning and perception.
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- **NPU-Optimized Architecture** – Uses ReLU ops, sparse tensors, convolutional layers, and static graph execution for maximum throughput — **20% faster than non-NPU-aware models** .
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- **Hardware-Aware Attention** – Attention patterns tuned for NPU, lowering compute and memory demand .
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- **Native Static Graph** – Supports variable-length multimodal inputs with stable, predictable latency .
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- **Performance Gains** – **9× faster audio processing** and **3.5× faster image processing** on NPUs compared to baseline encoders .
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- **Privacy-First Inference** – All computation stays local: private, offline-capable, and cost-efficient.
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---
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## **Performance / Benchmarks**
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### Human Evaluation (vs baselines)
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- **Vision**: Wins/ties in ~75% of prompts against Apple Foundation, Gemma-3n-E4B, Qwen2.5-Omni-3B.
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- **Audio**: Clear lead over baselines, much better than Gemma3n and Apple foundation model.
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- **Text**: Matches or outperforms leading multimodal baselines.
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<p align="center">
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<img src="https://cdn-uploads.huggingface.co/production/uploads/6618e0424dbef6bd3c72f89a/vsrg43GxTOSAj7q_SI60o.png" width="1560" alt="Human eval chart" />
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</p>
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### Nexa Attention Speedups
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- **9× faster** audio encoding (vs Whisper encoder).
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- **3.5× faster** image encoding (vs SigLIP encoder).
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<p align="center">
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<img src="https://cdn-uploads.huggingface.co/production/uploads/6618e0424dbef6bd3c72f89a/1039SN5JBQkS04z4YnoIi.png" width="400" alt="Human eval chart" />
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</p>
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---
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## **Architecture Overview**
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OmniNeural’s design is tightly coupled with NPU hardware:
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- **NPU-friendly ops** (ReLU > GELU/SILU).
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- **Sparse + small tensor multiplications** for efficiency.
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- **Convolutional layers** favored over linear for better NPU parallelization.
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- **Hardware-aware attention** patterns to cut compute cost.
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- **Static graph execution** for predictable latency.
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---
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## **Production Use Cases**
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- **PC & Mobile** – On-device AI agents combine **voice, vision, and text** for natural, accurate responses.
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- Examples: Summarize slides into an email (PC)*, *extract action items from chat (mobile).
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- Benefits: Private, offline, battery-efficient.
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- **Automotive** – In-car assistants handle **voice control, cabin safety, and environment awareness**.
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- Examples: Detects risks (child unbuckled, pet left, loose objects) and road conditions (fog, construction).
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- Benefits: Decisions run locally in milliseconds.
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- **IoT & Robotics** – Multimodal sensing for **factories, AR/VR, drones, and robots**.
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- Examples: Defect detection, technician overlays, hazard spotting mid-flight, natural robot interaction.
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- Benefits: Works without network connectivity.
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---
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## How to use
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> ⚠️ **Hardware requirement:** OmniNeural-4B currently runs **only on Qualcomm NPUs** (e.g., Snapdragon-powered AIPC).
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> Apple NPU support is planned next.
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### 1) Install Nexa-SDK
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- Download and follow the steps under "Deploy Section" Nexa's model page: [Download Windows arm64 SDK](https://sdk.nexa.ai/model/OmniNeural-4B)
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- (Other platforms coming soon)
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### 2) Get an access token
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Create a token in the Model Hub, then log in:
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```bash
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nexa config set license '<access_token>'
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```
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### 3) Run the model
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Running:
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```bash
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nexa infer NexaAI/OmniNeural-4B
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```
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/mic mode. Once the model is running, you can type below to record your voice directly in terminal
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```bash
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> /mic
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```
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For images and audio, simply drag your files into the command line. Remember to leave space between file paths.
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---
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## Links & Community
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[](https://discord.com/invite/nexa-ai)
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[](https://x.com/nexa_ai)
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[](https://nexa.ai)
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- **Issues / Feedback:** Use the **HF Discussions** tab or submit an issue in our discord or nexa-sdk github.
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- **Roadmap & updates:** Follow us on X and Discord.
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> If you want to see more **NPU-first, multimodal** releases on HF, please give our model a like ❤️.
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## Limitation
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The current model is mainly optimized for English. We will optimize other language as the next step.
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---
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## **Citation**
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```bibtex
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@misc{
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title={OmniNeural: World’s First NPU-aware Multimodal Model},
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author={Nexa AI},
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year={2025},
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url={https://huggingface.co/NexaAI/OmniNeural-4B},
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}
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```
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