AI chip selection recommendations and comparisons
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2026 H2 is the richest era for the AI compute market: NVIDIA Rubin R200, AMD MI400, Trainium 3, TPU 8t/8i, Ascend 920, and Groq 3 LPX are all in place. This article provides a complete selection tree to help you choose the most suitable product based on model size, training/inference, latency requirements, budget, and region.
2026 AI compute enters the "rack-scale" era. Single-chip comparisons have receded, and full-rack solutions have become the main battleground. This article provides an in-depth comparison of the five major rack-scale solutions: NVIDIA Rubin NVL72/NVL576, AMD Helios, Groq 3 LPX, AWS Trn3 UltraServer, and Google TPU 8t pod.
Apple Silicon is staging a comeback in the AI era. The M3 Ultra in a single Mac Studio packs 192GB unified memory (UMA) and an 80-core GPU, capable of running 70B-200B parameter LLMs locally without quantization. This is a revolution in consumer/workstation-class AI inference. This article provides an in-depth analysis of Apple Silicon's AI advantages, current ecosystem, and future.