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Apple Silicon Comeback: M3 Ultra 192GB UMA Local LLM Revolution

· 8 min read
Industry Research Team

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.

NVIDIA Acquires Groq for $20 Billion: LPU Officially Enters the NVIDIA Ecosystem

· 4 min read
Industry Research Team

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.

AWS Trainium 3 GA: 3nm Process + 4.4× Compute + 4× Efficiency + 144-Chip UltraServer

· 4 min read
Industry Research Team

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.

Huawei Ascend 920: China's Highest Bandwidth at 4 Tbps + 3× H20 Compute for Domestic Substitution

· 5 min read
Industry Research Team

Huawei Ascend 920 (昇腾 920) entered large-scale mass production in 2025 H2, representing a major breakthrough for Chinese domestic AI chips. This article analyzes its specifications, comparison with NVIDIA H20, the CloudMatrix 384 Ultra system, and its significance for China's AI industry.

China AI Chip Landscape 2025: Ascend, Cambricon, Hygon — Who Will Dominate?

· 5 min read
Industry Research Team

Escalating U.S. export controls are forcing China's AI chip industry to accelerate self-reliance. By 2025, the discussion around domestic Chinese AI chips has shifted from "are they usable?" to "which one should I choose?"

This article systematically reviews the major players, core products, and actual deployment status of domestic AI chips, helping developers and procurement decision-makers understand the competitive landscape.

GPU vs NPU vs TPU: In-Depth Comparison of Three AI Accelerator Architectures — Which One Should You Use?

· 5 min read
Industry Research Team

The AI accelerator chip space has three major mainstream architectures: GPU, NPU, and TPU. Add the recently emerging LPU (Language Processing Unit), and many developers find it hard to tell them apart.

This article compares them across four dimensions: architectural design philosophy, ecosystem maturity, real-world performance, and deployment cost.