Скачать или смотреть NVIDIA vs. Apple: The SHOCKING Truth About Local AI!

Stop wasting money on the wrong hardware! Is your NVIDIA RTX 4090 actually enough for the latest LLMs, or is Apple Silicon's Unified Memory the secret winner? In this video, we break down the definitive AI hardware comparison between NVIDIA, AMD, and Apple for 2025.
We dive deep into why VRAM is the critical factor for local AI—it is the "floor" of your system; if the model doesn’t fit, performance is irrelevant,. We explore:
• NVIDIA vs. AMD vs. Apple Silicon: Which titan actually rules the silicon war?,
• The VRAM Bottleneck: Why 24GB might not be enough for models like Llama 3.1 405B or DeepSeek R1,.
• Memory Bandwidth vs. Core Count: Why core count has diminishing returns for local inference,.
• New Tech: How NPUs and software like PowerInfer are making consumer-grade GPUs act like server-grade A100s,.
• Quantization (4-bit vs 8-bit): How to squeeze massive models into limited hardware,.
Whether you are building an AI PC for privacy, cost, or sovereignty, this guide ensures your investment isn't a "locality mismatch",.
Keywords: Local AI, AI Hardware, NVIDIA RTX 5090, Apple M4 Max, Unified Memory, VRAM, LLM Inference, CUDA vs ROCm, PowerInfer, NPU vs GPU, Llama 3, DeepSeek R1, Quantization, ForgeNEX.