local AI
14 stories tagged local AI.
Dual DGX Spark Matches Pricier AI Clusters in Testing
Level1Techs tests a dual DGX Spark against a far more expensive RTX Pro 6000 cluster—and the results challenge assumptions about what local AI actually costs.
30 GitHub Trending Projects Reshaping AI Agent Workflows
30 GitHub Trending Projects Reshaping AI Agent Workflows
GitHub Trending Weekly #45 surfaces 30 open-source projects revealing how developers are wrestling control, trust, and oversight back from AI agents.
audio.cpp Aims to Be a Local Runtime for Audio AI
audio.cpp Aims to Be a Local Runtime for Audio AI
audio.cpp is a new open-source C++ project attempting to unify local audio AI—TTS, STT, voice cloning—into one binary. Here's what it can and can't do yet.
How a 26B AI Model Now Runs in 2GB of RAM on a Mac
How a 26B AI Model Now Runs in 2GB of RAM on a Mac
A 26-billion-parameter model running in ~2GB of active RAM on a MacBook isn't magic. It's two independent timelines finally crashing into each other.
PrismML's Bonsai 27B Brings Qwen to Consumer Hardware
PrismML's Bonsai 27B Brings Qwen to Consumer Hardware
PrismML's Bonsai 27B runs Qwen 3.6 27B on 10GB of RAM using ternary compression. Here's what the benchmarks show—and what they don't.
Local AI's Inflection Point: Useful, Not Just Interesting
Local AI's Inflection Point: Useful, Not Just Interesting
A panel of local AI builders at NVIDIA, Roboflow, Exo Labs, and r/LocalLLaMA maps where the movement stands—and what still needs solving.
Gemma 4 12B Brings Local Agentic AI to Laptops
Gemma 4 12B Brings Local Agentic AI to Laptops
Google's Gemma 4 12B is a multimodal local AI model built for real agentic workflows on 16GB laptops—here's what the architecture actually means.
Can AMD Finally Compete for Local AI Workloads?
Can AMD Finally Compete for Local AI Workloads?
AMD's ROCm platform has quietly matured. Sam Witteveen tests a Threadripper + Radeon AI Pro workstation on LLMs, image gen, and training. Here's what he found.
Ternary Models Promise Full AI Power at Fraction of Size
Ternary Models Promise Full AI Power at Fraction of Size
PrismML's new ternary models claim to deliver FP16-level AI accuracy at 7-8x smaller size. We examine what's real and what's still theoretical.
TurboQuant Makes 16GB Macs Actually Useful for AI
TurboQuant Makes 16GB Macs Actually Useful for AI
New compression tech lets budget Macs run large language models that previously required 128GB. Here's what actually changed and what it means for you.
Intel's B70 GPU: Where Hardware Promise Meets Software Reality
Intel's B70 GPU: Where Hardware Promise Meets Software Reality
Intel's Arc Pro B70 outperforms pricier competitors on paper, but the software stack tells a different story. Real-world benchmarks reveal what matters.
Google's Gemma 4: Local AI That Doesn't Need the Cloud
Google's Gemma 4: Local AI That Doesn't Need the Cloud
Google's Gemma 4 brings cloud-level AI to your laptop. Free, offline, commercially usable—but is local AI ready to replace the cloud model?
Google's Gemma 4 Brings Powerful AI to Consumer Hardware
Google's Gemma 4 Brings Powerful AI to Consumer Hardware
Google released Gemma 4 under Apache 2.0 license. The open model runs on standard GPUs, challenging the assumption you need enterprise hardware for capable AI.
How to Run Massive AI Models on a MacBook Air
How to Run Massive AI Models on a MacBook Air
LM Studio's new remote access feature lets you run 480B parameter models from a 16GB MacBook Air. Here's how it actually works in practice.