Introducing AutoNeural-VL-1.5B: The first production-grade, real-time multimodal model for Qualcomm SA8295P NPU, pushing the boundaries of automotive AI performance It sees, understands, and acts locally detecting child movements, reading road signs, and ensuring real-time…
When AI Really Sees. 👀 This model gives the cockpit true spatial reasoning. With 768² high-res vision and <100ms Time-to-First-Token (TTFT), it's the closest I've seen to eye contact understanding from an in-cabin AI. Instantly detects complex parking signs, recognizes…
The Real Assistant. 🤝 This is where the Vision + Language Fusion shines. It moves beyond simple commands to semantic chaining. Example: It reads a party message on CarPlay, identifies the time/location, auto-starts navigation, and sends a precise ETA reply. From vision to…
Built for the Edge. 🏔️ Forget downsized LLMs. This is a ground-up, NPU-native design for the Qualcomm SA8295P, running completely on the neural processing unit (NPU). This guarantees: 1. Offline performance (works perfectly with no signal) 2. Privacy (data stays local) 3.…
Know More about: HuggingFace Model: huggingface.co/NexaAI/AutoNeu… ArXiv: arxiv.org/pdf/2512.02924 Web Page (Demos): nexa.ai/solution/intel… GitHub Repo: github.com/NexaAI/nexa-sd…
Running multimodal inference on-device at that scale opens up some genuinely wild possibilities for latency-critical safety systems.
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