FunctionGemma: The On-Device AI Revolution for Privacy-First Function Calling
3 days ago 高效码农FunctionGemma: A Lightweight Open Model Specialized for Function Calling What is FunctionGemma, and why does it matter for building local AI agents? FunctionGemma is a specialized variant of the Gemma 3 270M parameter model, finely tuned specifically for function calling tasks. It serves as a strong foundation for developers to create custom, fast, and private on-device agents that convert natural language inputs into structured API executions. Abstract illustration of open source AI model with circuit connections Image source: Public web illustration representing open AI concepts This model stands out because it prioritizes efficiency on resource-constrained devices while maintaining high performance …
How to Run LLMs on MediaTek Phones Using LiteRT-NeuroPilot
13 days ago 高效码农MediaTek NPU × LiteRT: Running LLMs on Phones Without Losing Your Sanity A field-note style walkthrough of the new LiteRT NeuroPilot Accelerator—what it is, why it matters, and how to ship a 1B-parameter model in an Android APK in under 30 min. 0. One-Sentence Take-away You can now compile a Gemma 3 1B model once and run it on millions of MediaTek phones at 1 600 tokens/s prefill—without writing a single line of SoC-specific C++—thanks to the LiteRT NeuroPilot Accelerator. 1. Why On-Device LLMs Keep Getting Stuck 1 cm from the Finish Line Core question: “I already have an INT8 …
Supertonic TTS: The Lightning-Fast On-Device Text-to-Speech Revolution in 2025
1 months ago 高效码农Supertonic: The Lightning-Fast, Fully On-Device TTS That Actually Works in 2025 Core Question: What exactly is Supertonic, and why is it running 100–167× faster than real-time on a laptop or phone — completely offline? Supertonic is a 66-million-parameter text-to-speech (TTS) model released by Supertone in 2025. Built for extreme on-device performance and powered by ONNX Runtime, it runs 100% locally on everything from smartphones to browsers — no cloud, no API keys, no privacy trade-offs. With just 2 inference steps it already sounds production-ready, and on Apple M4 Pro it hits an insane 167× real-time speed. Why Supertonic Changes Everything: …
Granite 4.0 Nano Models: The Future of Lightweight AI for Edge Devices
1 months ago 高效码农Granite 4.0 Nano Language Models: The Powerful Capabilities and Practical Guide to Lightweight AI What Are Granite 4.0 Nano Language Models? If you’re looking for an AI model that can run efficiently on devices with limited resources while still supporting a variety of complex tasks, Granite 4.0 Nano Language Models might be exactly what you need. Developed by IBM, these are lightweight, state-of-the-art open-source foundation models designed specifically for scenarios where efficiency and speed are critical. Unlike large-scale models that require massive computing resources, Granite 4.0 Nano can operate on resource-constrained hardware such as smartphones and IoT (Internet of Things) …
SmolVLA: How Affordable AI Is Democratizing Robotics With Human-Like Understanding
6 months ago 高效码农SmolVLA: The Affordable Brain Giving Robots Human-Like Understanding “ Train on a single gaming GPU. Deploy on a laptop CPU. Control real robots at 30% faster speeds. Meet the efficient vision-language-action model democratizing robotics. Why Robots Need Multimodal Intelligence Imagine instructing a robot: “Pick up the red cup on the counter, fill it with water, and bring it to me.” This simple command requires synchronized understanding of: Vision (identifying cup position) Language (decoding “fill with water”) Action (calculating joint movements for grasping/pouring) Traditional approaches train separate systems for perception, language processing, and control – resulting in complex, expensive architectures. Vision-Language-Action …
MiniCPM Real-Time Multimodal AI: Redefining Edge Device Intelligence
7 months ago 高效码农MiniCPM: A Breakthrough in Real-time Multimodal Interaction on End-side Devices Introduction In the rapidly evolving field of artificial intelligence, multimodal large models (MLLM) have become a key focus. These models can process various types of data, such as text, images, and audio, providing a more natural and enriched human-computer interaction experience. However, due to computational resource and performance limitations, most high-performance multimodal models have traditionally been confined to cloud-based operation, making it difficult for general users to utilize them directly on local devices like smartphones or tablets. The MiniCPM series of models, developed jointly by the Tsinghua University Natural Language …