12 stories tagged Local AI
AIPCs.store, a sister site of AInformed, benchmarks real computers on local AI models and publishes every result. It pairs the data with a calculator that estimates whether a model fits on your machine and how fast it will run.
Meta has released Muse Glimmer, an open-source AI agent designed to run locally on consumer hardware. It is multimodal, agentic, and customizable, enabling text generation, image creation, and complex workflows without sending data to the cloud.
Liquid AI released LFM2.5-2.6B, an open-source framework that lets users deploy AI agents on their own devices, ensuring privacy and full data control.
AMD's new Ryzen AI Halo brings powerful AI capabilities to your home computer, but it comes with a hefty price tag of $4,000. This system is designed to run AI models locally, offering privacy and speed benefits.
A Hacker News user asks for recommendations on local LLMs under 2 billion parameters that consume less than 3GB of RAM. The post currently has no answers or comments.
ParseHawk is a new open-source tool that extracts structured data from PDFs and images without needing the cloud. It's designed for developers and businesses that need to process documents locally.
Hugging Face released Holo3.1, a free open-source tool that lets you run AI agents locally. This means you can use AI assistants without sending your data to the cloud.
A new open-source AI model is designed to run locally and help detect cyber threats. It's small, specialized, and built for everyday users to protect their devices.
MLJAR Studio is a new desktop app that lets users analyze data via natural language, generating Python code and saving the session as a reusable notebook. The tool runs locally and supports cross-platform environments.
A comprehensive guide for running large language models on a 64GB RAM device has been released. It covers practical tips for optimizing performance in code and math applications.
Graeme (@gkisokay) shares a curated list of powerful local LLMs that run efficiently on 32GB RAM machines. This opens up flagship-class models to a wider range of users.
A curated list of small LLMs optimized for 16GB RAM devices, including Qwen3.5 9B and others. These models balance performance and efficiency for daily use.