Skip to main content

They go up to 4,266 MHz the Trident Z memories G.Skill

A clock frequency of 4.266 MHz certified by the producer: this is the result which came with new memories G.Skill Trident Z family DDR4 standard.

This kit is composed of two modules of 8 Gbytes of capacity each, certified to operate with CAS latency 19 to 4,266 MHz. They are part of this family also have two other kits designed to be used on more limited frequencies but with timings far more driven: the first it operates at a clock frequency of 3200 MHz with CL13 while the second clock of 3,466 MHz with latency equal to CL14.

The chips used are Samsung 8 Gbit each, while the cooling system is matched to that of the other modules of the family Trident Z: a massive plate, which is spread more of the memories of PCBs in height, with a marginal graphical characterization.

The memories from 4,266 MHz are only available in dual channel kits from 8 Gbytes of capacity per module; versions to 3.200 MHz and 3.466 MHz clock are also sold in configuration to 4 modules, the variable capacity of 8 to 16 Gbytes per module. The memories are of course compatible with Intel-based platforms Z170 chipset, combined with the XMP 2.0 technology; the supply voltage is equal to 1.35V, an upper 0,15V value than that of JEDEC for DDR4 modules.

Comments

Popular posts from this blog

The Silent Revolution of On-Device AI: Why the Cloud Is No Longer King

Introduction For years, artificial intelligence has meant one thing: the cloud. Whether you’re asking ChatGPT a question, editing a photo with AI tools, or getting recommendations on Netflix — those decisions happen on distant servers, not your device. But that’s changing. Thanks to major advances in silicon, model compression, and memory architecture, AI is quietly migrating from giant data centres to the palm of your hand. Your phone, your laptop, your smartwatch — all are becoming AI engines in their own right. It’s a shift that redefines not just how AI works, but who controls it, how private it is, and what it can do for you. This article explores the rise of on-device AI — how it works, why it matters, and why the cloud’s days as the centre of the AI universe might be numbered. What Is On-Device AI? On-device AI refers to machine learning models that run locally on your smartphone, tablet, laptop, or edge device — without needing constant access to the cloud. In practi...

Apple’s AI Push: Everything We Know About Apple Intelligence So Far

Apple’s WWDC 2025 confirmed what many suspected: Apple is finally making a serious leap into artificial intelligence. Dubbed “Apple Intelligence,” the suite of AI-powered tools, enhancements, and integrations marks the company’s biggest software evolution in a decade. But unlike competitors racing to plug AI into everything, Apple is taking a slower, more deliberate approach — one rooted in privacy, on-device processing, and ecosystem synergy. If you’re wondering what Apple Intelligence actually is, how it works, and what it means for your iPhone, iPad, or Mac, you’re in the right place. This article breaks it all down.   What Is Apple Intelligence? Let’s get the terminology clear first. Apple Intelligence isn’t a product — it’s a platform. It’s not just a chatbot. It’s a system-wide integration of generative AI, machine learning, and personal context awareness, embedded across Apple’s OS platforms. Think of it as a foundational AI layer stitched into iOS 18, iPadOS 18, and m...

Billionaire clothing dynasty heiress launches Everybody & Everyone to make fashion sustainable

Veronica Chou’s family has made its fortune at the forefront of the fast fashion business through investments in companies like Michael Kors and Tommy Hilfiger . But now, the heiress to an estimated $2.1 billion fortune is launching her own company, Everybody & Everyone , to prove that the fashion industry can be both environmentally sustainable and profitable. There’s no argument about the negative impacts of the fashion industry on the environment. The textiles industry primarily uses non-renewable resources — on the order of 98 million tons per year. That includes the oil to make synthetic fibers, fertilizers to grow cotton, and toxic chemicals to dye, treat, and produce the textiles used to make clothes. The greenhouse gas footprint from textiles production was roughly 1.2 billion tons of CO2 equivalent in 2015 — more than all international flights and maritime shipments combined (and a lot of those maritime shipments and international flights were hauling clothes). The lit...