Tagged "onnx"
22 articles tagged onnx, 14 February 2026 to 10 September 2026. Newest first.
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UNIST Develops On-Device AI That Cuts Model Storage 2,400-Fold
Researchers at UNIST have developed a breakthrough technique for on-device AI that reduces model storage requirements by 2,400 times, enabling deployment of capable models on severely resource-constrained edge devices.
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CPU vs GPU vs NPU: Which Semiconductor Does What?
A technical breakdown comparing CPUs, GPUs, and NPUs (Neural Processing Units) and their respective roles in AI inference. This educational piece helps practitioners understand hardware trade-offs when selecting platforms for local LLM deployment.
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Liquid AI Ships LFM2.5-230M with Broad Framework Support for On-Device Inference
Liquid AI released LFM2.5-230M, a compact language model optimized for local deployment across llama.cpp, MLX, vLLM, SGLang, and ONNX. This multi-framework support enables seamless on-device inference across diverse hardware and deployment scenarios.
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Chrome Quietly Downloads 4GB AI Model for Local Processing
Google Chrome begins automatically downloading a 4GB AI model to enable local LLM inference directly in the browser. This marks a shift toward on-device AI processing without explicit user permission.
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Qualcomm Reveals Snapdragon C with Advanced On-Device AI Engine
Qualcomm announces Snapdragon C processor featuring a 6nm process, optimised core configuration, and dedicated on-device AI accelerator. The chip targets mobile and edge devices for local AI inference.
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Chrome Silently Downloads 4GB AI Model for Local Inference Without User Consent
Google Chrome is automatically downloading a 4GB AI model to enable on-device inference capabilities, raising important questions about local storage, bandwidth usage, and user transparency in mainstream browser-based LLM deployment.
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Zoho-Backed Netrasemi Launches 12nm AI Chip, Mass Production Begins This Year
India's Netrasemi, backed by Zoho, is launching a 12nm AI processor with mass production starting in 2026, offering a homegrown option for local LLM inference with implications for edge deployment and hardware accessibility.
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Snapdragon C Debuts with 6nm Process and Dedicated On-Device AI Engine
Qualcomm's new Snapdragon C processor features a 6nm manufacturing process with a 1+3+4 CPU configuration and integrated on-device AI capabilities, enabling efficient local LLM inference on mobile and edge devices.
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MediaTek Dimensity 7500 Brings On-Device AI and Enhanced Power Efficiency to Mid-Range Phones
MediaTek's Dimensity 7500 processor integrates dedicated on-device AI capabilities with improved power efficiency, making local LLM inference accessible on affordable mid-range smartphones and expanding deployment possibilities.
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Privacy-Focused Raspberry Pi Zero 2W DIY Security Camera with On-Device AI and End-to-End Encryption
A new Raspberry Pi Zero 2W-based security camera project demonstrates practical on-device AI inference with end-to-end encryption, showcasing edge deployment on ultra-low-power hardware.
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Anker Soundcore Liberty 5 Pro Earbuds Feature Dedicated On-Device AI Chip with Touch Screen
Anker's new earbuds integrate a dedicated AI chip enabling on-device processing for voice commands and AI features, demonstrating consumer-grade hardware optimization for edge inference in form-factor-constrained devices.
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Show HN: Interactive and Stylized AI Chat Chrome Extension
A new Chrome extension demonstrates interactive and stylized AI chat capabilities, showing how local or edge-deployed inference can be integrated directly into browser workflows for improved user experience. This project highlights practical implementations of on-device AI for end users.
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Google's Gemma 4: Powerful AI Models Optimized for Your Phone and Laptop
Google introduces Gemma 4, a new generation of AI models specifically engineered for efficient on-device inference on phones and laptops. These models represent a major step forward in bringing capable language models to edge devices without cloud dependencies.
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Show HN: Turn Photos Into Wordle Puzzles with AI That Runs 100% in Your Browser
A practical demonstration of running computer vision and generative AI models entirely in-browser without server-side processing, showcasing the feasibility of edge AI inference for consumer applications.
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Ask HN: What do you use for local embeddings?
Community discussion on Hacker News exploring the best tools and approaches for running embedding models locally without external API dependencies.
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Ultra-Large 400B-Class LLM Runs on iPhone in Test
A 400B-parameter language model has been successfully demonstrated running on an iPhone, marking a significant breakthrough in on-device inference capabilities. This achievement suggests that ultra-large models can now fit and execute on consumer mobile devices through advanced optimization techniques.
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Show HN: Voice-tracked teleprompter using on-device ASR in the browser
A new browser-based tool that combines on-device automatic speech recognition with teleprompter functionality, enabling voice-tracked presentations without server dependencies. The system processes audio locally in the browser.
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Show HN: TLDR – Free Chrome Extension for AI-Powered Article Summarization
A new Chrome extension uses AI to generate two-second summaries of any article. The project demonstrates feasibility of running inference efficiently enough for real-time browser integration.
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AMD Expands Ryzen AI 400 Series Portfolio for Consumer and Enterprise AI PC Options
AMD announced an expanded lineup of Ryzen AI 400 Series processors, bringing more hardware options for local AI inference across consumer laptops and business workstations. The expansion increases accessibility of dedicated NPU hardware for on-device LLM deployment.
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Future of Mobile AI: What On-Device Intelligence Means for App Developers
An analysis of how on-device LLM inference is reshaping mobile app development, from privacy and latency benefits to new UX patterns. The article explores practical implications for developers building AI-powered mobile experiences.
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Same INT8 Model Shows 93% to 71% Accuracy Variance Across Snapdragon Chipsets
Testing reveals significant accuracy variance (93% to 71%) when deploying identical INT8 models across different Snapdragon SoCs, highlighting critical mobile deployment considerations.
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GPT-OSS 20B Now Runs 100% Locally in Browser via WebGPU
GPT-OSS 20B can now run entirely in web browsers using WebGPU acceleration through Transformers.js v4 and ONNX Runtime Web, enabling client-side AI without server dependencies.