Nexa SDK

Nexa SDK is a cutting-edge Software Development Kit designed to streamline the deployment of artificial intelligence models across a wide array of devices and platforms. It empowers developers to bring advanced AI capabilities, from large language models (LLMs) to multimodal vision-language models (VLMs) and computer vision, directly to edge devices such as mobile phones, PCs, IoT devices, and automotive systems. The SDK emphasizes production-ready on-device inference, ensuring high performance, energy efficiency, and reliability for real-world applications.

How to use Nexa SDK

Getting started with Nexa SDK is designed to be fast and straightforward. Developers can begin by downloading the Nexa CLI, which allows for instant testing and running of any model with just one line of code in the terminal, setting up in under 60 seconds. For rapid prototyping, the CLI can spin up a local OpenAI-compatible API. To integrate AI capabilities into applications, developers can deploy the SDK into their projects on various platforms including Windows, macOS, Linux, Android, and iOS. For mobile development, Nexa SDK provides simple Kotlin/Java APIs for Android and dedicated documentation for iOS, enabling on-device AI inference with minimal code (e.g., 3 lines for mobile deployment).

Core Features of Nexa SDK

• Universal Deployment: Ship any AI model to any device (PC, mobile, IoT, automotive) across CLI, Python, Android, Linux, Windows, macOS, and iOS.
• Hardware Acceleration: Optimized for NPU (Qualcomm, Apple, AMD, Intel), GPU, and CPU, delivering over 5x faster performance and >9x more energy efficiency on NPUs compared to SOTA solutions.
• Extensive Model Support: Run frontier and state-of-the-art models including LLMs (Mistral, Gemma, Qwen, Llama), VLMs, OCR, ASR, Embedding, Reranker, Object Detection, and Image Generation models (GGUF, MLX, SDXL).
• NexaQuant Model Compression: Proprietary compression method that shrinks models by 4x with near-zero accuracy loss (99% accuracy retained), fitting large models into mobile/edge RAM.
• Enterprise-Grade Optimization: Offers quantization-aware finetuning, Multi-LoRA for domain-specific capabilities, and Nexa Converter for private, in-house model optimization and conversion to NexaML-optimized artifacts.
• Developer-Friendly APIs: CLI for quick starts, Python SDK, and simple Kotlin/Java APIs for Android, with an OpenAI-compatible API for prototyping.

Use Cases for Nexa SDK

Nexa SDK is ideal for developers and enterprises looking to integrate advanced AI directly into their products, ensuring privacy, low latency, and offline functionality. Specific use cases include building on-device LLM copilots for notes, documents, and messages; developing multimodal understanding applications that process on-screen content, camera input, and files offline; implementing private, low-latency speech recognition features without cloud streaming; and deploying sophisticated AI models in automotive cockpits, IoT devices, and robotics platforms for real-time intelligence at the edge.

Advantages of Nexa SDK

The primary advantages of Nexa SDK lie in its unparalleled performance, broad compatibility, and developer-centric design. It enables developers to deploy cutting-edge AI models faster and more efficiently than ever before, leveraging specialized hardware for significant speed and energy savings. The SDK's ability to run SOTA models on-device, combined with NexaQuant's compression technology, allows for the creation of powerful yet lightweight applications. Its enterprise features provide robust tools for customization, privacy, and scalable deployment, making it a trusted solution for production-grade AI at the edge.