Two hundred models. Say it out loud and people glaze over. The trick is starting from the machine, not the model: answer three questions, GPU, VRAM, use case, and most of the two hundred just vanish. - The 7B class is the laptop sweet spot: writing, summarizing, coding help, general chat, offline. - Quantization stores weights in fewer bits, trading a little quality for a lot less memory. 4-bit is the default advice for local runs. - Match the model to the job, not the leaderboard. A prose-lovely model can be mediocre at code. - Benchmarks are a filter, not a verdict. Shortlist from hardware, test with your own prompts. Skip the DIY? PrivateLLM deploy sets up your private LLM on AWS for $50 plus usage. Your data never leaves your cloud.