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.
May 14, 2026, Intel disclosed in its Q1 earnings report that it has formally cancelled the Falcon Shores single-chip GPU project and confirmed a new rack-scale AI system project named Jaguar Shores to launch in 2027-2028. This is a major strategic adjustment in Intel's AI roadmap. This article provides an in-depth analysis of the reasons and future implications.
LLM inference performance = Algorithm + Software + Hardware. Hardware (H100, B300, Rubin) only determines the theoretical ceiling. Actual inference performance can be improved 5-30× through algorithmic optimization. This article provides a deep analysis of the three major inference optimization technologies: PagedAttention, FlashAttention, and Speculative Decoding.
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.
In 2026, AMD launched MI400 (CDNA Next) + Helios 72-GPU rack, AMD's flagship solution targeting NVIDIA NVL72. This article analyzes MI400's key specifications, the Helios rack's open interconnect (UALoF) strategy, and a comparison with Rubin R200.
On April 22, 2026, at the Cloud Next conference, Google unveiled TPU 8t + TPU 8i — splitting TPU into two independent product lines for the first time. TPU 8t focuses on training, TPU 8i on inference. This is a key product adjustment as Google responds to the AI inference era.
The NVIDIA Vera Rubin platform is NVIDIA's next-generation flagship computing platform after Blackwell. This article provides an in-depth analysis covering the naming origin, 6-chip packaging, memory subsystem, compute matrix, networking architecture, rack-scale solution, and software ecosystem.
On April 17, 2026, Cerebras Systems formally filed its S-1 prospectus with the SEC, applying to list on Nasdaq, targeting May 2026. This is one of the most significant IPOs in the AI chip industry in 2026. This article provides a deep analysis of Cerebras's finances, strategy, customers, and future.
In Q1 2026, one of the biggest pieces of news in the AI chip industry: NVIDIA acquired Groq for approximately $20 billion in a full acquisition. This means Groq's LPU architecture officially becomes part of NVIDIA's compute landscape, complementing GPUs. This article analyzes the strategic significance of this acquisition in detail.
On December 2, 2025, at the re:Invent 2025 conference, AWS formally GA'd its third-generation custom AI training chip Trainium 3. This is a critical upgrade to the AWS compute landscape: 3nm process, 4.4× compute improvement, 4× efficiency improvement, Trn3 UltraServer with 144 chips. This article provides a detailed analysis.