Nexa SDK abstracts the complexity of deploying AI models across heterogeneous devices by providing a unified runtime that automatically detects and routes workloads to the optimal hardware accelerator. Whether a device has an Apple Neural Engine, Snapdragon NPU, discrete GPU, or only a CPU, the NexaML runtime layer handles backend selection transparently. Developers write inference code once and deploy across PCs, smartphones, IoT devices, and wearables without platform-specific modifications.
The SDK provides day-zero compatibility with frontier open models including Qwen, Gemma, Llama, DeepSeek, and IBM Granite variants. It covers text generation, vision-language understanding, speech-to-text, text-to-speech, and image generation across all supported platforms. The OpenAI-compatible server mode enables serving local models through standard API endpoints, making it possible to use familiar chat interfaces and function-calling patterns without cloud dependencies.
Platform-specific SDKs are available for Python and C++ on desktop and server environments, native Android and iOS for mobile development, and Docker containers for Linux and IoT edge deployments. ARM SIMD kernels ensure efficient inference on resource-constrained devices, while zero-copy computation graphs minimize memory overhead. For organizations building privacy-sensitive applications in healthcare, finance, or enterprise contexts, Nexa SDK provides the infrastructure to keep all data processing on-device while maintaining the quality of modern AI capabilities.
