Gigabyte today announced the launch of AI TOP AERO, a new AI desktop powered by the NVIDIA RTX Spark platform. Positioned as a Personal AI Studio, AI TOP AERO combines an NVIDIA Blackwell architecture GPU, up to 128 GB of unified system memory, and Gigabyte's cooling and compact chassis design. The new desktop expands Gigabyte's AI PC lineup, bringing local AI development, content creation and gaming to personal workspaces.

NVIDIA RTX Spark unites NVIDIA AI, RTX graphics, and unified memory in one slim, powerful Windows PC. Designed to run larger AI models locally--without cloud dependency--and move between creative work, development, and immersive gaming without missing a beat. Connect apps, tools, and workflows into one seamless experience. Private by default. RTX Spark brings NVIDIA's full-stack AI platform, ready for the AI workloads of today and whatever comes next. Delivered on the familiar, trusted Windows platform.

NVIDIA today announced the availability of NVIDIA RTX Spark laptops, bringing together RTX graphics and NVIDIA's full-stack AI platform in slim, premium Windows PCs for accelerated creation, immersive gaming and powerful local AI—rolling out from ASUS, Dell, HP, Lenovo, Microsoft and MSI.

Combining decades of NVIDIA innovation into a single superchip, RTX Spark delivers up to 128 GB of unified memory and 1 petaflop of FP4 AI performance to run large language models and AI agents locally. On a single device, creators, developers and gamers can move seamlessly between their everyday workflows and emerging AI agents on the familiar Windows platform.

MSI, a global leader in high-performance and AI computing, today announced that the Prestige N16 Flip AI+ is now available for pre-order through MSI-certified partners in select markets.

Prestige N16 Flip AI+ is powered by NVIDIA RTX Spark, uniting NVIDIA AI, RTX graphics, and unified memory in one powerful and efficient thin-and-light Windows PC. Designed to run larger AI models locally—without cloud dependency—and move between creative work, development, and immersive gaming without missing a beat. Connect apps, tools, and workflows into one seamless experience. Private by default. RTX Spark brings NVIDIA's full-stack AI platform, ready for the AI workloads of today and whatever comes next. Delivered on the familiar, trusted, and secure Windows platform.

At IFA today, NVIDIA confirmed that the upcoming N1X SoC for the RTX Spark PC platform will come in two configurations. The top-end model will feature a 20-core "Grace" CPU and a GPU with 6,144 CUDA cores based on the "Blackwell" microarchitecture. NVIDIA envisions this version for both laptops and mini PCs, offering between 24 GB and 128 GB of LPDDR5X unified memory. The second configuration is slightly less powerful, with an 18-core "Grace" CPU, a "Blackwell" GPU with 5,120 CUDA cores, and 24-32 GB of LPDDR5X unified memory. This version is specifically aimed at laptops, which will be classified as Copilot+ AI PCs running Windows 11 for Arm.

Both chips are officially called "N1X," and there is no "N1" as previously thought. They are simply different configurations of the same chip, likely due to binning efforts during production. NVIDIA will launch these chips next month, and we expect to see systems from Acer, ASUS, Dell, MSI, HP, Microsoft, Lenovo, and many other OEMs. Pricing details are currently unknown, but with more memory, we can expect higher prices from any OEM, as memory is currently the most scarce resource.

At IFA 2026, Acer showcased its unique take on the new NVIDIA RTX Spark desktop PC platform with a new chassis. In a package Acer calls the SFF RTX Spark, likely emphasizing the small-form-factor of this PC, the design differs from previous DGX Sparks. The RTX naming convention focuses more on home office users, creators, gamers, and local AI enthusiasts. The SFF RTX Spark from Acer features up to a 6,144-core GeForce RTX "Blackwell" GPU, alongside up to 20 cores on the NVIDIA "Grace" CPU, delivering a total of 1 PetaFLOPS of FP4 compute power. The entire package can be configured with up to 128 GB of LPDDR5X unified memory, all running on the Windows 11 desktop operating system.

Acer used a black shroud with a single bronze accent, providing an elegant and edgy design. The system can stand on its own in a horizontal position, while there is a specific holder for a vertical position, as shown in the images below. NVIDIA's full optimization stack for gaming and local AI is included, along with Acer's customizations that are typically featured in the company's PCs and laptops.

Acer showcased the Acer SFF RTX Spark design for a compact desktop powered by the NVIDIA RTX Spark superchip at Acer's next@Acer global press conference on September 2 during IFA 2026. NVIDIA RTX Spark redefines personal computing, combining personal agents, advanced content creation and high-performance gaming in a new platform engineered from the ground up for the next wave of Windows PC experiences. Designed for creators, AI developers and gamers, NVIDIA RTX Spark brings NVIDIA's full-stack AI platform and full suite of RTX technologies to compact desktops.

Powered by NVIDIA RTX Spark at its core, the Acer SFF RTX Spark offers major compute power in a space-saving footprint for tapping into agentic AI running locally. The design is built to deliver up to 1 petaflop of AI performance and up to 128 GB of high-speed unified memory, delivering a combination of compute and data privacy. It features up to a 6,144-core Blackwell RTX GPU, up to a 20-core NVIDIA Grace CPU, up to 1 petaflop of AI compute, and up to 128 GB of unified memory, paired with NVIDIA's full-stack AI platform and full suite of RTX technologies to accelerate AI innovation at the edge.

NVIDIA has released a technical details on its next-generation "Rubin" GPU, including a fully annotated die shot. "Rubin" represents a significant generational leap in NVIDIA's mission to scale computing across numerous racks, systems, and data centers. The company is promoting this generation as the first "agentic AI" native design. This AI paradigm means that inference workloads are continuously active, engage in reasoning, planning, tool utilization, and execute many sequential steps. In this context, inference refers to a completed model running on the GPUs, rather than being trained, which is what Rubin is designed for. NVIDIA claims up to 10x more agentic throughput per unit of energy compared to "Blackwell." This improvement relies not only on the new "Vera" CPU and rack-level power management but also on the entire system, as customers now prioritize overall system performance rather than just the performance of a single GPU.

In its full configuration, "Rubin" combines two compute dies in a single package, linked with a high-speed connection that NVIDIA calls NV-HBI. This chiplet approach uses CoWoS-L packaging from TSMC, chosen because each die is already as large as the chip factory can print in one go, reaching the reticle limit. The GPU contains 336 billion transistors, up to 224 SMs, 896 Tensor Cores with a third-generation Transformer Engine, and 288 GB of HBM4 memory, capable of delivering up to 50 PetaFLOPS of inference and about 35 PetaFLOPS of training at the ultra-compact NVFP4 format. This is NVIDIA's proprietary 4-bit data format that enhances efficiency in inference and training with minimal to no accuracy loss compared to the 8-bit and 16-bit data formats used today for training and inference. However, this is quite different from the FP16/FP32 formats used in gaming GPUs. Below, we will break down not just the GPU, but the entire platform NVIDIA has built around it.

Today, HP Inc. announced its latest devices and solutions, designed to enable developers of all types to create new experiences using AI. HP is previewing PCs powered by NVIDIA RTX Spark, bringing a reinvention of personal computing, combining personal agents, advanced content creation, and high-performance gaming in a new platform engineered from the ground up for the next wave of Windows PC experiences.

"Developers are moving from experimenting with AI to shipping agentic applications, and they need PCs that are as open, fast, and flexible as their workflows," said Samuel Chang, Senior Vice President and Division President, Consumer Personal Systems at HP Inc. "Our expanded portfolio pairs compact, powerful hardware with pre-configured environments and open-source toolchains to eliminate setup friction and accelerate the path from idea to execution. Whether it is a device optimized for hybrid Windows workflows, creators, gamers, or AI practitioners or powerful workstations for edge development, we're giving builders a clear, practical path to run local agents and scale hybrid AI with confidence."

When NVIDIA first revealed DLSS 5 and its neural rendering, a lot of the online backlash that was leveled at the feature centered around Capcom's Resident Evil character, Grace, and how DLSS 5 changed her facial features. Now, in a recent interview with Eurogamer, Koshi Nakanishi and Masato Kumzawa, the game's director and producer, have responded to the DLSS 5 outrage and to the game's overall reception at and since launch. Addressing the DLSS 5 debacle, Kumzawa took the backlash as a positive indication, commenting that "the fact a lot of players commented they really liked the original design of Grace and didn't want to see it changed was a positive—it meant we got the design right," and that it was an indication that "Grace quickly established herself as a fan favorite." The Nakanishi and Kumzawa did not comment on previous allegations that Capcom had not involved game developers or even inform them of the potential changes to the character designs ahead of time.

[Editor's note: Our in-depth review of Resident Evil Requiem can be found here]

Just 16 days after Resident Evil Requiem launched, it had already sold over 6 million units, making it the fastest-selling Resident Evil game to date. Commenting on the overall success of the game, the pair said that "we were very happy to see the reaction of players around the world after the game launched. In particular, because we were very tight-lipped in order to maintain the surprise for players, especially about what happens after the return to Raccoon City. So, watching people's clips and online reactions, we felt not only pleased that they were enjoying it, but relieved our strategy was right to try and save that for them." Notably, the Resident Evil developer publicly asked gamers not to spoil surprises about the game when the game's plot was leaked online shortly before the official launch.

MSI announced that its next-generation AI platform, MSI EdgeXpert, has officially become an NVIDIA-Certified System. This validation ensures the hardware has undergone rigorous testing by NVIDIA engineers for performance, functionality, scalability, and security. Most importantly, it brings MSI EdgeXpert into the supported ecosystem of NVIDIA AI Enterprise (NVAIE), strengthening its capability to support enterprise-grade generative AI, AI agents, and high-performance edge AI workloads.

Establishing Hardware Trust Standards through Rigorous Testing
NVIDIA-Certified Systems establish a broad hardware trust standard. MSI EdgeXpert has passed extensive evaluations, including deep learning training with TensorFlow and PyTorch, high-throughput inference with TensorRT and Triton, and system-level security testing. While the certification covers a wide range of hardware reliability, its support for NVIDIA AI Enterprise is one of the most significant values, helping organizations move efficiently from proof of concept to real-world deployment.

MSI, a global leader in high-performance server solutions, today unveils its latest AI infrastructure portfolio built on NVIDIA's modular architectures, including the NVIDIA MGX platform and NVIDIA DGX Station technology. Designed to accelerate AI training, large-scale inference, HPC, edge, and next-generation data center workloads, MSI's expanded lineup delivers exceptional scalability, performance density, and deployment flexibility.

Scalable AI Infrastructure Built on NVIDIA MGX Architecture
Leveraging the modular design of NVIDIA MGX architecture, MSI has developed a comprehensive portfolio of 4U and 6U liquid-cooled servers supporting NVIDIA RTX PRO 6000 Blackwell Server Edition and NVIDIA RTX PRO 4500 Blackwell Server Edition GPUs. The NVIDIA MGX architecture enables flexible CPU selection, high-capacity memory configurations, and seamless integration of high-speed networking - empowering enterprises to deploy infrastructure tailored to diverse workload requirements, from data center deployments to edge applications.

Giga Computing, a subsidiary of GIGABYTE and a leader in accelerated computing and infrastructure solutions, today announced new enterprise AI solutions that support NVIDIA Vera CPU and NVIDIA Vera Rubin platform, well as a new AI factory in Taiwan. The GIGABYTE booth at NVIDIA GTC shows scalable AI solutions that not only focus on performance and efficiency but also incorporate the software and infrastructure needed to build AI factories and other large GPU clusters. The GIGABYTE booth staff is ready to introduce the latest hardware and software for success in deploying accelerated computing.

Personal AI Supercomputers
With products spanning all segments of the supercomputer space, Giga Computing showcases professional desktop and deskside solutions that are ideal for AI development and accelerating AI training and inference workloads. These solutions are being used by data scientists and researchers in research institutions, government agencies, and enterprises.

Dell Technologies (NYSE: DELL) today announces support for NVIDIA NemoClaw and NVIDIA OpenShell, expanding its collaboration with NVIDIA to advance secure, autonomous AI agents. For developers working locally, Dell and NVIDIA are teaming up on NVIDIA NemoClaw—an open source stack that simplifies running OpenClaw always-on assistants, more safely, with a single command. As part of the NVIDIA Agent Toolkit, it installs the NVIDIA OpenShell, an open source runtime providing a secure environment for running autonomous agents, and open source models like NVIDIA Nemotron.

Dell Pro Max with GB10 and GB300 provide purpose-built desktop platforms that allow enterprises to build and run autonomous, self-evolving agents locally with frontier-level intelligence. As the first OEM to ship a desktop with NVIDIA GB300 Grace Blackwell Ultra Desktop Superchip, Dell brings 20 petaFLOPS of performance and 748 GB of memory directly to developers' desks.

Once a target of the largest industry acquisition that was halted by market regulators, NVIDIA has officially divested all its holdings in Arm Holdings PLC by selling 1.1 million shares, valued at about $140 million at the time of writing. Importantly, this does not end the NVIDIA-Arm relationship, as NVIDIA continues to be a customer and partner, licensing Arm IP and its instruction set for its older "Grace" and newer "Vera" CPUs. If readers recall, NVIDIA announced in late 2020 that it was acquiring Arm Ltd. in a deal valued at $40 billion. However, regulators from the UK and EU blocked the deal to preserve fair market competition, citing concerns that the NVIDIA-Arm deal would harm competition and stifle innovation. NVIDIA even paid a break-up fee of $1.25 billion as the deal collapsed under regulatory pressure.

As mentioned, NVIDIA's partnership with Arm is not limited to investment or stock ownership, as the company utilizes its IP and instruction set across a range of products. For example, NVIDIA has Arm-based SoCs in various forms in its embedded computing unit with Jetson modules and mini-computers that power everything from robotics to automated driving development in modern vehicles. Additionally, NVIDIA recently began offering its "Vera" CPUs as standalone server CPUs designed to compete with the industry's latest and greatest x86-based designs from AMD and Intel, demonstrating that NVIDIA is serious about being an Arm ISA licensee for the foreseeable future, not just viewing the company as an investment target.

Many portable PC enthusiasts welcomed Dell's very recent restoration of familiar XPS model naming convention; replacing generically confusing "Premium" monikers. Unfortunately, back-dated leaks still mention the latter—as evidenced by one of Olrak29's latest shipping manifest discoveries. A November 20 entry lists a Dell 16 Premium model powered by NVIDIA's still-in-progress N1X system-on-a-chip. According to leaks from last year, this "Grace Blackwell" APU utilizes twenty Arm CPU cores and an iGPU specced with 48 compute units. Hopeful Team Green supporters looked forward to a possible official unveiling at last week's CES trade event, but an eventual non-showing (occupying second place on TPU's top five) led to much disappointment.

Apparently, the GB10 Superchip forms the basis of N1 and N1X SoCs—the same tech has been deployed in NVIDIA's extremely expensive DGX Spark AI mini desktop PC. For the moment, Qualcomm's mainstream Snapdragon X chips are keeping Arm-based solutions alive on Windows 11 Arm with Copilot+. A July 2025 rumor posited that teething problems had prompted a major delay of the N1-series project, with a revised launch period supposedly marked down for late 2026. The November shipping manifest mentions an "ES2" designation, likely implying that Dell was playing around with N1X engineering samples.

Korean tech publication Hankyng reports that Samsung Electronics has secured a deal to supply half of NVIDIA's SOCAMM2 modules in 2026. NVIDIA designed its upcoming "Vera Rubin" Superchip module, which consists of two "Rubin" AI GPUs and one "Vera" CPU, to support DDR5 SOCAMM2 modules. These replace hardwired LPDDR5X ECC memory found in current "Grace Blackwell" Superchip modules. SOCAMM2, or small-outline CAMM2, is a variant of DDR5 CAMM2 modules with slimmer outlines, to further minimize their PCB footprint. Replacing 512-bit LPDDR5X on Grace with 8-channel (16 sub-channel) DDR5 on Vera allows for higher densities that are further upgradeable, and higher clock speeds.

ASUS has announced that, in collaboration with the National Center for High-performance Computing (NCHC) to build the new AI supercomputer, the facility is now officially in operation. It features a dual-compute architecture that includes the cluster and the latest NVIDIA GB200 NVL72 system—Taiwan's first fully liquid-cooled AI supercomputer deployment of this architecture. The Nano4 NVIDIA HGX H200 system delivers up to 81.55 PFLOPS of performance and is ranked No. 29 on the TOP500 list, marking a meaningful milestone in strengthening Taiwan's AI-computing capabilities and accelerating its intelligent transformation.

NCHC spokesperson Dr. Chia-Lee Yang said: "As the designer of the Nano4, NCHC drove the architecture, liquid-cooling strategy, and system integration. Along with AI-infrastructure expertise from ASUS, this newly built system feeds advanced computes for generative AI, big data, deep learning, and HPC, unlocking unprecedented computational capabilities for both academia and industry."

SK hynix showcased advanced memory technologies for the era of AI and high-performance computing (HPC) at Supercomputing 2025 (SC25), held in St. Louis, the U.S., from November 16-21. Held annually since 1988, SC is the world's largest global HPC conference. It brings together experts from industry, academia, and research institutions to share the latest trends, create opportunities for collaboration, and discuss the future direction of technological advancement. At this year's event, the convergence of AI and HPC emerged as a central topic. Under the theme "Memory, Powering AI and Tomorrow," SK hynix presented its innovative memory lineup set to lead the AI and HPC markets and shared a new technological vision to accelerate data analysis in computing systems.

Innovative Products and Tech Driving AI and HPC Performance
At the event, SK hynix presented core products including HBM, DRAM, and eSSD solutions. Visitors to the booth could also see demonstrations of the products in AI and HPC environments, highlighting the company's technological competitiveness. At the front of the booth, SK hynix displayed its latest HBM products including the 12-layer HBM4 which it developed as a world-first in September 2025. HBM4 features 2,048 input/output (I/O) channels, twice that of the previous generation, delivering a significant increase in bandwidth. Also offering more than a 40% boost in power efficiency, HBM4 is the most suitable solution for ultra-high-performance AI computing systems. In addition, the 12-layer HBM3E, the highest performing commercialized HBM currently available on the market, was presented with NVIDIA's next-generation GB300 Grace Blackwell GPU.

SK hynix shared its next-generation AI memory strategy and roadmap at the SK AI Summit 2025 held in Seoul from November 3-4. At the summit held under the theme "AI Now & Next," the company elevated its vision from becoming a full-stack AI memory provider to embracing a broader role as a full-stack AI memory "creator." Hosted annually by SK Group, the event was formerly known as the SK Tech Summit but has evolved with a greater focus on AI to become the SK AI Summit since 2024. This year's event brought together global AI experts and industry professionals to discuss the present and future of AI technologies, as well as its applications across industries.

Among those in attendance were SK Group Chairman Chey Tae-won, SK hynix CEO Kwak Noh-Jung, and SK Telecom CEO Jung Jaihun. They were joined by influential tech leaders including OpenAI CEO Sam Altman and Amazon CEO Andy Jassy, who delivered keynote speeches via video. Furthermore, global tech giants including NVIDIA, Amazon Web Services (AWS), Google, TSMC, and Meta, together with numerous domestic members of the K-AI Alliance, participated to discuss collaboration opportunities across the AI ecosystem.

The 66th edition of the TOP500 list of the world's most powerful supercomputers was announced today at the SC25 Conference in St Louis, Missouri. The new list reflects continued U.S. leadership in high-performance computing (HPC), historic European milestones, and growing global diversity across architectures and energy-efficient design.

El Capitan Extends Leadership Across Benchmarks
The El Capitan system at Lawrence Livermore National Laboratory (LLNL) remains the undisputed leader of global HPC. Based on the HPE Cray EX255a architecture, powered by AMD 4th Gen EPYC CPUs and AMD Instinct MI300A accelerators, El Capitan achieved 1.809 Exaflop/s on the HPL benchmark—a significant remeasurement that further strengthens its position as the fastest computer in the world. El Capitan also dominates the HPCG benchmark, delivering 17.41 HPCG-Petaflop/s, making it the #1 for real-world application performance. On the HPL-MxP mixed-precision benchmark, it recorded 16.7 Exaflop/s, confirming its versatility in AI and data-driven workloads. With 11.34 million cores and an energy efficiency of 60.9 GFlops/Watt, El Capitan exemplifies the current generation of exascale computing.

Today Microsoft, NVIDIA and Anthropic announced new strategic partnerships. Anthropic is scaling its rapidly-growing Claude AI model on Microsoft Azure, powered by NVIDIA, which will broaden access to Claude and provide Azure enterprise customers with expanded model choice and new capabilities. Anthropic has committed to purchase $30 billion of Azure compute capacity and to contract additional compute capacity up to one gigawatt.

For the first time, NVIDIA and Anthropic are establishing a deep technology partnership to support Anthropic's future growth. Anthropic and NVIDIA will collaborate on design and engineering, with the goal of optimizing Anthropic models for the best possible performance, efficiency, and TCO, and optimizing future NVIDIA architectures for Anthropic workloads. Anthropic's compute commitment will initially be up to one gigawatt of compute capacity with NVIDIA Grace Blackwell and Vera Rubin systems.

Super Micro Computer, Inc. (SMCI), a Total IT Solution Provider for AI/ML, HPC, Cloud, Storage, and 5G/Edge, will showcase its latest AI Factory, HPC, and liquid-cooled data center innovations at Supercomputing 2025 (SC25) in St. Louis, Missouri. This broad portfolio, ranging from desktop workstations to rack-scale solutions, demonstrates Supermicro's commitment to powering the next generation of high-performance computing, scientific research, and enterprise AI deployments.

"Supermicro continues to lead the industry in delivering complete, next-generation infrastructure solutions in close collaboration with our technology partners," said Charles Liang, president and CEO of Supermicro. "At SC25, we are demonstrating our high-performance DCBBS architecture, direct liquid cooling, and rack-scale innovations, which empower customers to deploy AI and HPC workloads faster, more efficiently, and more sustainably."

NVIDIA's "Blackwell Ultra" server racks are undoubtedly powerful, but they demand significant system cooling. NVIDIA promotes the GB300 NVL72 as the top configuration: these liquid-cooled racks, built with Grace Blackwell Ultra Superchips, achieve exascale-class dense FP4 performance and offer substantial improvements in throughput-per-megawatt compared to previous HGX platforms. However, this extreme performance mandates massive cooling systems, which can cost around $50,000. According to a valuation model from investment bank Morgan Stanley, NVIDIA is spending nearly $50,000 on cooling for the 72-GPU configuration within its Oberon rack. With each chip rated at 1,400 W TDP, traditional air-based cooling solutions are not feasible.

Considering that there are 72 GPUs rated up to 1,400 W, that is over 100 kW from GPUs alone. Add 32 "Grace" CPUs that are powering the system, and you have more than a 100 kW of heat at the peak load. Morgan Stanley models the rack as containing 18 compute trays (each consuming roughly 6.6 kW but needing cooling for about 6.2 kW) alongside nine switch trays. The firm values the cooling components for a single compute tray at about $2,260, which multiplies to roughly $40,680 across the rack. Switch-tray cooling adds about $1,020 per tray, or $9,180 total. High-performance cold plates are singled out as the most expensive parts in the BOM, with per-unit prices in the low hundreds.

AI factories continue to grow at unprecedented scale, processing structured, unstructured and emerging AI-native data. With demand for trillion-token workloads exploding, a new class of infrastructure is required to keep pace. At NVIDIA GTC Washington, D.C, NVIDIA revealed the NVIDIA BlueField-4 data processing unit, part of the full-stack BlueField platform that accelerates gigascale AI infrastructure, delivering massive computing performance, supporting 800 Gb/s of throughput and enabling high-performance inference processing.

Powered by software-defined acceleration across AI data storage, networking and security, NVIDIA BlueField-4 transforms data centers into secure, intelligent AI infrastructure—designed to accelerate every workload, in every AI factory. It's purpose-built as the end-to-end engine for a new class of AI storage platforms, bringing AI data storage acceleration to the foundation of AI data pipelines for efficient data processing and breakthrough performance at scale.

NVIDIA today announced that it is working with the U.S. Department of Energy's national labs and the nation's leading companies to build America's AI infrastructure to support scientific discovery, economic growth and power the next industrial revolution.

"We are at the dawn of the AI industrial revolution that will define the future of every industry and nation," said Jensen Huang, founder and CEO of NVIDIA. "It is imperative that America lead the race to the future—this is our generation's Apollo moment. The next wave of inventions, discoveries and progress will be determined by our nation's ability to scale AI infrastructure. Together with our partners, we are building the most advanced AI infrastructure ever created, ensuring that America has the foundation for a prosperous future, and that the world's AI runs on American innovation, openness and collaboration, for the benefit of all."