Nexa SDK – Build powerful and efficient AI apps on edge devices
Hey HN! Alex and Zack here from Nexa AI. We're excited to share something we've been working on. Our journey began with the Octopus series --- action models for mobile AI agents (https://huggingface.co/NexaAIDev/Octopus-v2). We focused on making sub-billion parameter models excel at function calling, making high accurate and fast function-calling possible on mobile and edge devices. But as we delved into developing full-fledged on-device applications, we hit a roadblock. We realized that optimizing for function calling (tool-use) alone wasn't enough. Building powerful…
Nexa SDK – Build powerful and efficient AI apps on edge devices launched on September 8, 2024 with 27 votes, #699 of 5,281 launches that month and more than 75% of that year's launches. The site was still online in September 2026, 2 years on.
In plain words
Nexa SDK is a toolkit for building AI applications on mobile and edge devices. It combines language models, speech processing, image generation, and embedding models to enable developers to create full-featured on-device AI apps. The SDK builds on Nexa AI's work with small parameter models optimized for function calling on resource-constrained devices, providing the diverse tools needed beyond basic tool-use capabilities.
written from the facts on this page · September 2026
From the sources
Run frontier LLMs and VLMs locally on Qualcomm devices across NPU, GPU, and CPU with a few lines of code - qualcomm/GenieX
In the maker’s words, at launch
Hey HN! Alex and Zack here from Nexa AI. We're excited to share something we've been working on. Our journey began with the Octopus series --- action models for mobile AI agents (https://huggingface.co/NexaAIDev/Octopus-v2). We focused on making sub-billion parameter models excel at function…
Does a similar job
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Use functional tokens for AI agents to simplify app workflows2024 · nexa4ai.com · ▲80Hi HN! I want to share our latest project at NEXA AI. We developed AI agent foundation models designed to transform how developers create AI agent powered apps. One major challenge we've observed with current human-computer interactions is that many simple, one-step tasks become unnecessarily complex, multi-step workflows due to limitations of current GUIs. AI agents can solve this, but existing AI agent models are slow and costly. To tackle these issues, we built lightweight AI agent models based on our Octopus V2, small language models for function calling (You can learn more about our…
We built a knowledge hub for running LLMs on edge devices2024 · github.com · ▲13Hey HN! Alex and Zack from Nexa AI here. We are excited to share a project our team has been passionately working on recently, in collaboration with Jiajun from Meta, Qun from San Francisco State University, and Xin and Qi from the University of North Texas. Running AI models on edge devices is becoming increasingly important. It's cost-effective, ensures privacy, offers low-latency responses, and allows for customization. Plus, it's always available, even offline. What's really exciting is that smaller-scale models are now approaching the performance of large-scale closed-source models for…




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