Nexa SDK
Nexa SDK is an on-device inference framework that enables developers to run any AI model (text, image, audio, multimodal) locally across different devices and hardware backends with high performance and privacy.
https://sdk.nexa.ai/?ref=producthunt
Product Information
Updated:Oct 9, 2025
What is Nexa SDK
Nexa SDK is a developer-first toolkit designed to make AI deployment fast, private and accessible anywhere without being locked to the cloud. It is an on-device inference framework that supports running various types of AI models locally on CPUs, GPUs, and NPUs across different platforms including PC, mobile, automotive, and IoT devices. The SDK provides comprehensive support for multiple model formats like GGUF, MLX, and Nexa's own .nexa format, along with backend support for CUDA, Metal, Vulkan, and Qualcomm NPU.
Key Features of Nexa SDK
Nexa SDK is a comprehensive on-device AI inference framework that enables developers to run various AI models (including LLMs, multimodal, ASR, and TTS models) locally across multiple devices and backends. It supports multiple input modalities (text, image, audio), provides an OpenAI-compatible API server, and offers efficient model quantization for running on CPUs, GPUs, and NPUs with backend support for CUDA, Metal, Vulkan, and Qualcomm NPU.
Cross-Platform Compatibility: Runs on multiple platforms including macOS, Linux, Windows, with support for CPU, GPU, and NPU acceleration across various backends (CUDA, Metal, Vulkan, Qualcomm NPU)
Multiple Model Format Support: Compatible with various model formats including GGUF, MLX, and Nexa's own .nexa format, enabling efficient quantized inference
Multimodal Processing: Handles multiple input types including text, image, and audio with support for text generation, image generation, vision-language models, ASR, and TTS capabilities
Developer-Friendly Integration: Offers OpenAI-compatible API server with JSON schema-based function calling, streaming support, and bindings for Python, Android Java, and iOS Swift
Use Cases of Nexa SDK
Financial Services: Implementation of sophisticated financial query systems with on-device processing to ensure data privacy and security
Interactive AI Characters: Creation of local interactive AI characters with voice input/output and profile image generation capabilities without internet dependency
Edge Computing Applications: Deployment of AI models on edge devices and IoT hardware for real-time processing and reduced latency
Mobile Applications: Integration of AI capabilities in mobile apps with efficient resource utilization and offline functionality
Pros
Enables private, on-device AI processing without cloud dependency
Supports multiple platforms and hardware acceleration options
Offers efficient model quantization for resource-constrained devices
Provides developer-friendly tools and APIs
Cons
Some features like MLX are platform-specific (macOS-only)
Requires specific hardware for certain acceleration features (e.g., Snapdragon X Elite for Qualcomm NPU)
May have limitations in model compatibility and performance compared to cloud-based solutions
How to Use Nexa SDK
Install Nexa SDK: Run 'pip install nexaai' in your terminal. For ONNX model support, use 'pip install "nexaai[onnx]"'. Chinese developers can use Tsinghua Mirror by adding '--extra-index-url https://pypi.tuna.tsinghua.edu.cn/simple'
Check System Requirements: Ensure your system meets the requirements. For GPU acceleration, NVIDIA GPUs need CUDA Toolkit 12.0 or later. For NPU support, verify you have compatible hardware like Snapdragon® X Elite chip or Apple Silicon
Select Model: Browse available models from the Nexa Model Hub. Models support various tasks including text, image, audio, and multimodal processing. Filter based on your needs and hardware capabilities (CPU, GPU, or NPU support)
Run Model: Use one line of code to run your chosen model. Format: 'nexa run <model_name>'. For example: 'nexa run llama3.1' for text generation or 'nexa run qwen2audio' for audio processing
Configure Parameters: Adjust model parameters as needed including temperature, max tokens, top-k, and top-p for fine-tuned responses. The SDK supports JSON schema-based function calling and streaming
Handle Input/Output: Process inputs based on model type - text input for LLMs, drag-and-drop or file path for audio/image files. The SDK handles multiple input modalities including text 📝, image 🖼️, and audio 🎧
Optimize Performance: Use quantization techniques to reduce model size if needed. Choose appropriate bit counts based on your hardware capabilities and performance requirements
Access Support: Join the Discord community for support and collaboration. Follow on Twitter for updates and release notes. Contribute to the GitHub repository at github.com/NexaAI/nexa-sdk
Nexa SDK FAQs
Nexa SDK is an on-device inference framework that allows running AI models across different devices and backends, supporting CPUs, GPUs, and NPUs with backend support for CUDA, Metal, Vulkan, and Qualcomm NPU.
Nexa SDK Video
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