ViewTube

What local AI models can you run on a regular computer, without a powerful desktop GPU? I ran six LLMs, from 5B to 35B ...

Dip your toe into local AI at Micro Center, the AI destination: https://micro.center/322535 Austin, Texas: sign up now for a FREE ...

Supported systems can allocate up to 160GB as graphics memory, creating more room for large local AI models and longer ...

A person on Reddit asked those who spent more than $10000 on a local AI setup whether they regret it. Meanwhile a used RTX ...

Intel Arc B580 ($250, 12GB) runs local AI surprisingly fast. See real token/sec benchmarks, OpenVINO vs SYCL setup, and ...

Looking for the best GPU for your Local AI setup, LLM inference, or fine-tuning without overspending? In this video, we break ...

The open versions of Jev are here . In this video we go through 7 of the open Jev style models to see how good they are and what ...

M5 Ultra Mac Studio local AI speed, measured: tokens per second and prompt processing on Qwen 3.8 27B, against the M3 Ultra, ...

What is the cheapest, and most valuable, way to reach 48GB of memory for local AI in 2026? In this video, I compare nearly every ...

Bosgame M5 mini PC with 128GB unified memory: can a $2999 local AI desktop actually run 120B models faster than an RTX ...

Want to try for yourself? Find the code here → https://ibm.biz/~pDRvDsIfj Want to run an LLM on your own hardware? Cedric ...

Everyone knows an ordinary computer can load a small AI model today. But loading a model into memory is the easy part.

A $780 graphics card can leave less room for your coding model than an older mac mini. Your $1000 budget needs to buy the ...

A $200 a month AI subscription is $2400 a year. Running a model on your own GPU costs between 6 and 38 cents per million ...

If your own PC doesn't have a powerful GPU, this method can be useful for experimenting with larger local AI models without ...

RTX 5090 local AI inference just got up to 1.9× faster according to NVIDIA, thanks to new llama.cpp optimizations. But does that ...

We evaluate inference speed (~68–70 tokens/sec) of Ternary Bonsai 2 27B and put its agentic coding capabilities to the test with ...

Spark-X2.5-4B is a compact 4-billion parameter model configured with a native 1048576-token context window. While fitting a 4B ...

In this one, I set up a fully local, self-hosted LLM on my PC using Ollama — no cloud, no API calls, no data leaving my machine.

The first time you run a large language model on your own computer, it will be worse than the free one in your browser. It will be ...