Apple Silicon vs Nvidia

Описание: The "Memory Wall" has officially been demolished. In this video, we put the Apple M4 Ultra through the ultimate AI stress test. While NVIDIA dominates in raw tokens-per-second for smaller models, the M4 Ultra’s 32-core Neural Engine and support for up to 512GB of Unified Memory have made it the only choice for researchers running 400B+ parameter models on a single desktop.

We break down the 2026 performance data:

The Neural Engine Leap: We benchmark the 32-core ANE (2x M4 Max) in Core ML and MLX. Discover why the M4 Ultra is delivering 3x the AI throughput of the M1 Ultra in real-world stable diffusion and whisper-transcription tasks.

Unified Memory vs. VRAM: We demonstrate "The Impossible Load"—running Llama 3.1 405B (Q4 quantization) entirely in memory. We compare this to the multi-GPU "headaches" required to achieve the same on Windows.

MLX Optimization: A look at how Apple’s MLX framework has matured in 2026, narrowing the gap with CUDA and allowing the M4 Ultra to achieve over 20 tokens/second on 70B models.

The Efficiency Paradox: Measuring the M4 Ultra’s 190W peak draw against an RTX 5090 system’s 700W+. Is the "silent performance" worth the "Apple Tax"?

Whether you're an AI researcher, a creative pro using Generative Fill, or a developer building local-first agents, this is the definitive benchmark guide for Apple's most powerful silicon to date.

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