Run large language, multimodal, speech recognition, and text-to-speech models directly on mobile, desktop, automotive, and IoT devices, optimized for NPUs, GPUs, and CPUs.
Nexa AI is an on-device inference platform designed to run large language models (LLMs), multimodal models, automatic speech recognition (ASR), text-to-speech (TTS), and other AI/ML workloads directly on edge hardware. Its primary purpose is to deliver fast, private, and cost-efficient AI execution across mobile, PC, automotive, and IoT devices without relying heavily on cloud infrastructure. By targeting NPUs, GPUs, and CPUs, Nexa AI enables developers and OEMs to deploy advanced AI capabilities where data is generated.
The platform provides optimized runtimes and model execution pipelines that leverage heterogeneous compute, including dedicated AI accelerators as well as general-purpose processors. It supports quantization, model compression, and hardware-aware optimizations to reduce latency and power consumption while maintaining model accuracy. Nexa AI is built to handle multimodal scenarios, such as combining vision, speech, and language tasks, and can integrate with existing applications through SDKs and APIs. Its architecture is designed for low-latency inference, offline operation, and predictable performance across diverse device classes.
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