#hardware

Discover how DIY Raspberry Pi “philosopher” toys and high‑performance multi‑GPU setups let small businesses run large language models locally, keeping data in‑house for full privacy.

Could Nvidia stop the RTX 5090 to boost AI profits? Find out how the shift to enterprise GPUs could raise prices for gamers and reshape the GPU market.

Explore Vega, the new physics‑based decision model—open‑source, 800M‑4B parameter options, 73k‑token context, image support, and sub‑20 ms GPU latency.

Open‑source LumaBrowser lets you run LLMs, vision, and music models from a single Electron browser, auto‑managing memory and supporting agents, dashboards, and CLI tools.

Explore how the “Drifting” method trains Turkish TTS models on an RTX 5090 GPU, its live Hugging Face demo, and mixed user feedback on fluency and naturalness.

audio.cpp performance updates slash VRAM cuts boost local TTS speeds 48% for Higgs, 2x on CUDA/Vulkan, now 110+ models. Click to learn how.

Maximize LLM inference speed with high‑VRAM rigs and custom vLLM forks—discover why Qwen3.8‑Flash‑Next outperforms GLM‑5.3‑Flash in raw throughput yet GLM excels in task latency.

Explore the rise of ultra‑small LLMs like MacroStories and the niche 3‑B d1‑3B model—discover how parameter efficiency is reshaping AI deployment on CPUs and low‑resource systems.

New llama.cpp GPU cache speeds Mixture‑of‑Experts models on low‑VRAM GPUs, boosting local AI performance and keeping open‑source deployment competitive.

Explore a browser‑based O’Neill cylinder walk‑through and learn how sparse memory LLMs match larger models using SSD‑backed lookup tables—cutting VRAM and boosting speed.