Offline Privacy & On-Device AI Inference
Running local Large Language Models (Llama 3, Mistral, Qwen) using Ollama or LM Studio requires high memory bandwidth to prevent slow tokens-per-second generation.
1. Apple Silicon Macs (Unified Memory King)
MacBook Pro M3 Max (36GB / 48GB / 64GB Unified Memory) treats system RAM as shared GPU VRAM, allowing offline execution of 70B parameter quantized LLMs at high speed.
2. RTX Windows Laptops (Tensor Core CUDA Speed)
NVIDIA RTX 4070 / 4080 laptops with 16GB VRAM and 32GB system RAM accelerate PyTorch fine-tuning and local Stable Diffusion XL image generation via TensorRT.