Tracked topic
Qwen3 is an AI model family developed by Alibaba, released as a set of large language models for natural-language tasks.
…For LLMs, I'm running either qwen3.6:27b-q4_K_M or qwen2.5-coder:14b , both fitting within the available 20 GB of VRAM. Frigate and Immich don't require…
…Quiz 8 Questions · Test Your Knowledge Ollama & Local LLMs Trivia Challenge Think you know your way around running AI models locally — put your Ollama expertise to the test! Setup Models Commands Privacy…
…My Bachelor’s thesis was conducted on the viability of benchmarking the non-functional elements of Android apps and smartphones such as performance, and I’ve been working in the tech industry…
…This makes Gemma-4-E2B light enough to run on my NAS’ i5‐1235U CPU, and the LLM + LocalAI combo consumes about 6.2GB of memory when I actively prompt it. Performance…
Local LLMs perform so much better when you teach them to ask before they answer
…However, its extra performance overhead and lack of advanced tools became pretty apparent once I started looking into ways to maximize the efficiency on my local models. Once I started wanting to…
…The best part? FydeOS performs incredibly well on the Raspberry Pi. I’ll probably sound insane when I say this, but I’ve had better performance while running emulators and watching videos…
…with is Qwen 2.5 Coder 7B Instruct, which already has strong YAML and code generation capabilities out of the box for a model of its size. It performs well on HumanEval…
…Qwen 3.5 9B pulled through as expected My local setup is Qwen 3.5 9B through LM Studio. It uses GDN so my memory doesn't ramp up and I can…
…Alibaba's Qwen 3.6-27B arrived the same month as a dense workhorse that fits on a single consumer 24 GB GPU with quantization. Qwen 3.6-35B-A3B, the sparse…