Local LLM Gerçeği: M1 Air ile Hayal Kırıklığı Yaşadım
Everyone is talking about Local LLMs these days. As the cost of cloud AI tools like Claude and ChatGPT keeps increasing, I decided to see if I could replace them with models running entirely on my own machine. The plan was simple: ✅ Install Gemma 4 and Qwen 3.5 ✅ Build a benchmark environment ✅ Compare their coding capabilities ✅ Share the results with you Unfortunately, things didn’t go as expected. 😅 In this video, we talk about: • My real-world experience running Local LLMs on an M1 MacBook Air with 16 GB RAM • Why model size matters • What Parameters actually mean • What a Context Window is • What Quantization does • What Architecture (Arch) means • Why some models require tens or even hundreds of gigabytes of memory • What you should know before investing time in Local AI If you’re thinking about running AI models on your own computer, this video might save you a lot of time, frustration, and downloads.

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