Reviews praise Nexa SDK for fast local setup, smooth “build & ship” flow, and strong hardware flexibility across CPU/GPU/NPU with Apple and Qualcomm support. Users highlight privacy, low latency, and reliable performance for text, vision, audio, and image tasks, plus broad model format compatibility (GGUF, MLX, Gemma3n, PaddleOCR). Notably, the makers of
NexaAI emphasize unifying fragmented backends and future-proofing across devices. Feedback notes excellent docs, minimal configuration, and consistent performance from prototyping to production, making it a dependable choice for on‑device AI.
Octoverse
Hello Product Hunters! 👋
I’m Alex, CEO and founder of NEXA AI, and I’m excited to share Nexa SDK: The easiest On-Device AI Toolkit for Developers to run AI models on CPU, GPU and NPU
At NEXA AI, we’ve always believed AI should be fast, private, and available anywhere — not locked to the cloud. But developers today face cloud latency, rising costs, and privacy concerns. That inspired us to build Nexa SDK, a developer-first toolkit for running multimodal AI fully on-device.
🚨 The Problem We're Solving
Developers today are stuck with a painful choice:
- Cloud APIs: Expensive, slow (200-500ms latency), and leak your sensitive data
- On-device solutions: Complex setup, limited hardware support, fragmented tooling
- Privacy concerns: Your users' data traveling to third-party servers
💡 How We Solve It
With Nexa SDK, you can:
- Run models like LLaMA, Qwen, Gemma, Parakeet, Stable Diffusion locally
- Get acceleration across CPU, GPU (CUDA, Metal, Vulkan), and NPU (Qualcomm, Apple, Intel)
- Build multimodal (text, vision, audio) apps in minutes
- Use an OpenAI-compatible API for seamless integration
- Choose from flexible formats: GGUF, MLX
📈 Our GitHub community has already grown to 4.9k+ stars, with developers building assistants, ASR/TTS pipelines, and vision-language tools. Now we’re opening it up to the wider Product Hunt community.
Best,
Alex