ASUS Introduces Ascent GX10 Mini-PC Featuring NVIDIA’s GB10 Grace Blackwell Chip

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Meet the ASUS Ascent GX10: Your New AI Supercomputer

Today, ASUS has launched something truly exciting: the ASUS Ascent GX10, a revolutionary AI supercomputer that’s ready to bring serious computing power right to your desktop. At its core is the nVidia GB10 Grace Blackwell Superchip, which promises to change the game for developers, AI researchers, and data scientists worldwide.

As AI models become more complex and demanding, local development is increasingly challenging. Think about it: tuning and prototyping large models require not just skill but also a hefty amount of memory and computing power. That’s where the Ascent GX10 steps in, offering a robust and cost-effective solution for anyone diving into AI development.

Unmatched AI Performance at Your Fingertips

So, what can you expect from the ASUS Ascent GX10? Brace yourself for up to 1,000 TOPS of AI performance, which is more than enough to handle large AI workloads. With a whopping 128 GB of coherent unified system memory, developers can now experiment and fine-tune the latest reasoning AI models that boast up to 200 billion parameters—all from the comfort of their desks.

Powered by NVIDIA Grace Blackwell Technology

At the heart of the Ascent GX10 is the impressive NVIDIA GB10 Superchip, designed with the Grace Blackwell architecture in mind. This chip isn’t just powerful; it’s optimized for compact form factors, making it a perfect fit for desktop environments. With a robust Blackwell GPU featuring fifth-generation Tensor Cores and FP4 support, the GB10 delivers that jaw-dropping 1000 TOPS of AI processing power. Plus, it’s equipped with a high-performance 20-core ARM CPU that speeds up data preprocessing and orchestration, making model tuning and real-time inferencing a breeze.

What’s even more exciting is the integration of NVIDIA NVLink -C2C, which provides a seamless CPU+GPU memory model that boasts five times the bandwidth of PCIe 5.0. Talk about a game changer!

Tackling Large-Parameter Generative AI Models

The ASUS Ascent GX10 is not just about raw power; it’s also about capability. With its 128 GB of unified system memory and support for FP4 data formats, this supercomputer can handle AI models with up to 200 billion parameters. This means developers can prototype and fine-tune reasoning models with as many as 70 billion parameters right on their desktop. And if that’s not enough, two GX10 systems can be linked together using integrated NVIDIA ConnectX network interface cards (NICs) to tackle even larger models, like Llama 3.1, which boasts a staggering 405 billion parameters.

Local Development Meets Scalable Deployment

The Ascent GX10 is designed to be a powerful yet economical platform for AI experimentation. Developers can prototype models and applications without hogging essential compute resources in their clusters, which are better suited for training and deploying production models. Thanks to NVIDIA AI software, transitioning models from desktop environments to NVIDIA DGX Cloud or any accelerated cloud or data center infrastructure is nearly seamless—no major code adjustments required. This makes the whole process of prototyping, fine-tuning, and iteration so much easier.

Empowering the AI Community

“AI is transforming every industry, and the ASUS Ascent GX10 is designed to bring this transformative power to every developer’s fingertips,” said KuoWei Chao, General Manager of ASUS IoT and NUC Business Group. With the integration of the NVIDIA Grace Blackwell Superchip, ASUS is providing a compact yet powerful tool that empowers developers, data scientists, and AI researchers to innovate and push the boundaries of AI—all from their desks.

In a world where AI is becoming increasingly integral to our lives, the ASUS Ascent GX10 is poised to be a game changer. Are you ready to elevate your AI development experience?

Background Information

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About ARM:

ARM, originally known as Acorn RISC Machine, is a British semiconductor and software design company that specializes in creating energy-efficient microprocessors, system-on-chip (SoC) designs, and related technologies. Founded in 1990, ARM has become a important player in the global semiconductor industry and is widely recognized for its contributions to mobile computing, embedded systems, and Internet of Things (IoT) devices. ARM's microprocessor designs are based on the Reduced Instruction Set Computing (RISC) architecture, which prioritizes simplicity and efficiency in instruction execution. This approach has enabled ARM to produce highly efficient and power-saving processors that are used in a vast array of devices, ranging from smartphones and tablets to IoT devices, smart TVs, and more. The company does not manufacture its own chips but licenses its processor designs and intellectual property to a wide range of manufacturers, including Qualcomm, Apple, Samsung, and NVIDIA, who then integrate ARM's technology into their own SoCs. This licensing model has contributed to ARM's widespread adoption and influence across various industries.

  

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About ASUS:

ASUS, founded in 1989 by Ted Hsu, M.T. Liao, Wayne Hsieh, and T.H. Tung, has become a multinational tech giant known for its diverse hardware products. Spanning laptops, motherboards, graphics cards, and more, ASUS has gained recognition for its innovation and commitment to high-performance computing solutions. The company has a significant presence in gaming technology, producing popular products that cater to enthusiasts and professionals alike. With a focus on delivering and reliable technology, ASUS maintains its position as a important player in the industry.

  

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About nVidia:

NVIDIA has firmly established itself as a leader in the realm of client computing, continuously pushing the boundaries of innovation in graphics and AI technologies. With a deep commitment to enhancing user experiences, NVIDIA's client computing business focuses on delivering solutions that power everything from gaming and creative workloads to enterprise applications. for its GeForce graphics cards, the company has redefined high-performance gaming, setting industry standards for realistic visuals, fluid frame rates, and immersive experiences. Complementing its gaming expertise, NVIDIA's Quadro and NVIDIA RTX graphics cards cater to professionals in design, content creation, and scientific fields, enabling real-time ray tracing and AI-driven workflows that elevate productivity and creativity to unprecedented heights. By seamlessly integrating graphics, AI, and software, NVIDIA continues to shape the landscape of client computing, fostering innovation and immersive interactions in a rapidly evolving digital world.

  

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Technology Explained

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Blackwell: Blackwell is an AI computing architecture designed to supercharge tasks like training large language models. These powerful GPUs boast features like a next-gen Transformer Engine and support for lower-precision calculations, enabling them to handle complex AI workloads significantly faster and more efficiently than before. While aimed at data centers, the innovations within Blackwell are expected to influence consumer graphics cards as well

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CPU: The Central Processing Unit (CPU) is the brain of a computer, responsible for executing instructions and performing calculations. It is the most important component of a computer system, as it is responsible for controlling all other components. CPUs are used in a wide range of applications, from desktop computers to mobile devices, gaming consoles, and even supercomputers. CPUs are used to process data, execute instructions, and control the flow of information within a computer system. They are also used to control the input and output of data, as well as to store and retrieve data from memory. CPUs are essential for the functioning of any computer system, and their applications in the computer industry are vast.

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GPU: GPU stands for Graphics Processing Unit and is a specialized type of processor designed to handle graphics-intensive tasks. It is used in the computer industry to render images, videos, and 3D graphics. GPUs are used in gaming consoles, PCs, and mobile devices to provide a smooth and immersive gaming experience. They are also used in the medical field to create 3D models of organs and tissues, and in the automotive industry to create virtual prototypes of cars. GPUs are also used in the field of artificial intelligence to process large amounts of data and create complex models. GPUs are becoming increasingly important in the computer industry as they are able to process large amounts of data quickly and efficiently.

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Grace Blackwell: Grace Blackwell is a cutting-edge technology that has revolutionized the computer industry. It is a type of artificial intelligence that is designed to mimic human cognitive abilities, such as learning, problem-solving, and decision-making. This technology has been applied in various areas of the computer industry, including data analysis, natural language processing, and machine learning. For example, Grace Blackwell can analyze large amounts of data and identify patterns and trends, making it a valuable tool for businesses to make informed decisions. It can also understand and respond to human language, making it useful for virtual assistants and chatbots. Additionally, Grace Blackwell can continuously learn and improve its performance, making it an invaluable asset in the development of new technologies. Overall, Grace Blackwell has greatly enhanced the capabilities of computers and has opened up new possibilities for the future of technology.

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PCIe: PCIe (Peripheral Component Interconnect Express) is a high-speed serial computer expansion bus standard for connecting components such as graphics cards, sound cards, and network cards to a motherboard. It is the most widely used interface in the computer industry today, and is used in both desktop and laptop computers. PCIe is capable of providing up to 16 times the bandwidth of the older PCI standard, allowing for faster data transfer speeds and improved performance. It is also used in a variety of other applications, such as storage, networking, and communications. PCIe is an essential component of modern computing, and its applications are only expected to grow in the future.

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Tensor Cores: Tensor Cores are a type of specialized hardware designed to accelerate deep learning and AI applications. They are used in the computer industry to speed up the training of deep learning models and to enable faster inference. Tensor Cores are capable of performing matrix operations at a much faster rate than traditional CPUs, allowing for faster training and inference of deep learning models. This technology is used in a variety of applications, including image recognition, natural language processing, and autonomous driving. Tensor Cores are also used in the gaming industry to improve the performance of games and to enable more realistic graphics.

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