Budget homelabs test open-weight LLMs

The thread captures the current local-AI sweet spot: hobbyist boxes can do real work, but the margin between fun and full workstation is still memory bandwidth and dollars.

• –Llama 3.2's 1B/3B models and Google's guidance to start with Gemma 3 4B show that the true entry point is still tiny, not frontier-sized.
• –Qwen2.5's 7B/14B/32B ladder and Mistral NeMo 12B / Mistral Small 24B are the realistic next step when you have 32GB RAM and/or a modest GPU.
• –The best value remains a consumer GPU with 16GB+ VRAM plus system RAM; pure-CPU inference works, but latency kills the fun quickly.
• –If the goal is learning rather than replacing subscriptions, hosted access to open-weight models is the cheaper way to sample frontier systems before buying hardware.