Local LLM Deployment

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GGUF vs GPTQ vs AWQ: The Plain-English Guide to LLM Quantization (and Which One to Pick)

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Ollama 0.30 delivers faster NVIDIA GPU performance and wider hardware support

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alternativeto.net·

On-device AI is a margin decision

 🖥️Self-hosted apps  Content type: Blog
ziraph.com··Hacker News

KaiFelixBennett/gemma4-turboquant-rdna4: Run Gemma-4-31B at full 256K context on a $1,400 AMD RDNA4 GPU (gfx1201): TurboQuant KV cache + HIP-graph-safe Flash-Attention for llama.cpp, fully measured on real hardware.

 🗃️SQLite  Content type: Code
github.com··Hacker News

Fixing a stuck Ollama runner and building a GPU watchdog

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Gemma 4 QAT models: Optimizing model compression for mobile and laptop efficiency

 🖥️Self-hosted apps  Content type: News  Content type: Blog
blog.google··Hacker News

A system programmer’s guide to LLM inference

 🖥️Self-hosted apps  Content type: Blog

Show HN: Run Llama.cpp In-Process from Java with Project Panama FFM

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Less-relevant results

Apple WWDC On-Device AI Deep Dive - Google Docs

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gist.is··Hacker News

NexusOS v2.0 – A zero-dependency pipeline streaming server chaos to Parquet

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Running Qwen 35B MoE at 450k Context on a Single 32GB GPU

 🪟Awesome windows command-line

Looking Inside Chromium’s On-Device AI Stack

 🖥️Self-hosted apps  Content type: Blog
island.io··Hacker News

Integrate on-device AI models into your app using Core AI - WWDC26 - Videos

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Run (your largest) local models from your iPhone

 🗃️SQLite  Content type: Blog

Gemma 4 12B: A unified, encoder-free multimodal model

 🗃️SQLite  Content type: Discussion

Google’s DiffusionGemma is 4x faster than its other Gemma models

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thenewstack.io·

local AI agents for Cursor with pre-tuned marketplace/commu

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locaible.com··Hacker News

Omnifs: APIs and data sources as files you can ls, cat, grep, and pipe

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omnifs.dev··Hacker News

Apple Silicon's on-device AI bet hasn't moved – only the chip range that runs it

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Token4Token — pay-per-token inference on Gnosis + Swarm

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