According to a report from Wccftech, it’s indicated that with soaring market demand, the shipment volume of NVIDIA’s Blackwell architecture GB200 AI servers has also significantly increased.

As NVIDIA claims, the Blackwell series is expected to be its most successful product. Industry sources cited by Wccftech indicate that NVIDIA’s latest GB200 AI servers are drawing significant orders, with strong demand projected to continue beyond 2025. This ongoing demand is enabling NVIDIA to secure additional orders as its newest AI products remain dominant.

The increasing demand for NVIDIA GB200 AI servers has led to revenue performances of Taiwanese suppliers such as Quanta, Foxconn, and Wistron exceeding expectations. Reportedly, NVIDIA is expected to ship 60,000 to 70,000 servers equipped with GB200 AI server. Each server is estimated to cost between USD 2 million and 3 million, resulting in approximately USD 210 billion in annual revenue from the Blackwell servers alone.

NVIDIA’s GB200 AI chip servers, available in NVL72 and NVL36 specifications, have seen greater preference for the less powerful models due to the growing number of AI startups choosing the more financially feasible NVL36 servers.

Notably, according to the industry sources previously cited in a report from Economic Daily News, TSMC is gearing up to start production of NVIDIA’s latest Blackwell platform architecture graphics processors (GPU) on the 4nm process.

The same report further cited sources, revealing that international giants such as Amazon, Dell, Google, Meta, and Microsoft will adopt the NVIDIA Blackwell architecture GPU for AI servers. As demand exceeds expectations,NVIDIA is prompted to increase its orders with TSMC by approximately 25%.

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• [News] NVIDIA Reportedly Developing Tailored Version of the Blackwell Series for Chinese Market
• [News] TSMC Reportedly Sees Strong 4nm Demand, with NVIDIA’s Order Up by 25%

(Photo credit: NVIDIA)

According to the industry sources cited in a report from Economic Daily News, TSMC is gearing up to start production of NVIDIA’s latest Blackwell platform architecture graphics processors (GPU) on the 4nm process. In response to the strong customer demand, NVIDIA has reportedly increased its orders to TSMC by 25%.

This surge not only underscores the unprecedented boom in the AI market but also provides substantial momentum for TSMC’s performance in the second half of the year, setting the stage for an optimistic annual outlook adjustment, the report notes.

TSMC is set to hold an earnings conference call on July 18, in which it is expected to release the financial results of the second quarter as well as the guidance for the third quarter.

As TSMC will reportedly commence the production of NVIDIA’s Blackwell platform architecture GPU, which may be regarded as one of the most powerful AI chips, it is anticipated to be a focal point of discussion at TSMC’s upcoming earnings call.

Packed with 208 billion transistors, NVIDIA’s Blackwell-architecture GPUs are manufactured using a custom-built 4NP TSMC process with two-reticle limit GPU dies connected by 10 TB/second chip-to-chip link into a single, unified GPU.

The report further cited sources, revealing that international giants such as Amazon, Dell, Google, Meta, and Microsoft will adopt the NVIDIA Blackwell architecture GPU for AI servers. As demand exceeds expectations,NVIDIA is prompted to increase its orders with TSMC by approximately 25%.

As NVIDIA ramps up production of its Blackwell architecture GPUs, shipments of terminal server cabinets, including the GB200 NVL72 and GB200 NVL36 models, have seen a simultaneous significant increase. Initially expected to ship a combined total of 40,000 units, this figure has surged to 60,000 units, marking a 50% increase. Among them, the GB200 NVL36 accounts for the majority with 50,000 units.

The report estimates suggest that the average selling price of the GB200 NVL36 server cabinet is USD 1.8 million, while the GB200 NVL72 server cabinet commands an even higher price of USD 3 million. The GB200 NVL36 features 36 GB200 super chips, 18 Grace CPUs, and 36 enhanced B200 GPUs, whereas the GB200 NVL72 boasts 72 GB200 super chips, 36 Grace CPUs, and 72 B200 GPUs, which all contribute to TSMC’s momentum.

TSMC former Chairman Mark Liu, before handing over the reins in June, had already predicted that the demand for AI applications looks more optimistic compared to a year ago. Current Chairman C.C. Wei has also indicated that AI applications are just beginning, and he is optimistic like everyone else.

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• [News] End of an Era under Mark Liu’s Leadership, TSMC Discusses Future Development Plans
• [News] TSMC’s 4nm Process Powers NVIDIA’s Blackwell Architecture GPU, AI Performance Surpasses Previous Generations by Multiples

(Photo credit: TSMC)

During NVIDIA founder and CEO Jensen Huang’s keynote speech on June 2, he shared insights on how the AI era is driving the development of a new global industrial revolution.

According to a report from TechNews, he covered various technologies and application areas, including advancements in accelerated computing, microservices, industrial digitalization, and consumer devices, which are expected to become key focus areas in the evolving AI market.

• Accelerated Computing

1. Collaboration between the computer industry and NVIDIA to build AI factories and data centers: NVIDIA and leading computer manufacturers worldwide announced today the launch of a series of systems based on the NVIDIA Blackwell architecture. These systems feature Grace CPUs, NVIDIA networking technologies, and infrastructures to assist enterprises in establishing AI factories and data centers.

2. Foxconn utilizes NVIDIA artificial intelligence and Omniverse technology to train robots and streamline assembly operations: Foxconn operates over 170 plants worldwide, with its latest being a virtual plant driving the latest developments in industrial automation technology.

The latest of Foxconn’s plant is a digital twin model of a new factory in Guadalajara, Mexico, a hub for the electronics industry. Engineers at Foxconn define processes and train robots in this virtual environment to enable physical factories to efficiently produce the next generation of accelerated computing engines, the NVIDIA Blackwell HGX system.

3. NVIDIA significantly strengthens Ethernet networks for generative artificial intelligence: NVIDIA announced widespread adoption of the NVIDIA Spectrum-X Ethernet platform and will accelerate the release of new products. CoreWeave, GMO Internet Group, Lambda, Scaleway, STPX Global, and Yotta are the first batch of AI cloud service providers to adopt NVIDIA Spectrum-X, bringing ultimate network performance to their AI infrastructure.

Additionally, NVIDIA’s partners have also released products utilizing the Spectrum platform, including ASRock Rack, ASUS, GIGABYTE Technology, Ingrasys Inc., Inventec, Quanta Cloud Technology, Wistron and Wiwynn. Moreover, Dell Technologies, Hewlett Packard Enterprise, Lenovo, and Super Micro Computer have collaborated with NVIDIA to incorporate the Spectrum platform into their respective products.

• Microservices

NVIDIA NIM has revolutionized deployment model: NVIDIA has announced that its inference microservice, NVIDIA NIM, optimized in container form, is now available for download by 28 million developers worldwide.

This allows deployment to cloud, data centers, or workstations, enabling developers to effortlessly build generative artificial intelligence applications for assisting partners, such as copilots and chatbots, within minutes, a process that previously took several weeks.

• Industrial Digitalization

1. Electronics manufacturers adopt NVIDIA AI and Omniverse to drive robotic factories and accelerate industrial digitization: NVIDIA announced that major Taiwanese electronics manufacturers, including Delta Electronics, Foxconn, Pegatron Corporation, and Wistron Corporation, are using NVIDIA’s technology to transform their factories into more autonomous production facilities through new reference workflows.

This workflow combines NVIDIA Metropolis visual artificial intelligence (AI) technology, NVIDIA Omniverse’ physically accurate rendering and simulation technology, and NVIDIA Isaac’s AI robot development and deployment technology.

2. Industry leaders adopt NVIDIA’s robotic technology to develop tens of millions of AI-supported autonomous machines, including BYD Electronics, Siemens, Teradyne Robotics, and Alphabet’s Intrinsic, among more than ten global leading companies in the robotics industry.

These companies integrate NVIDIA Isaac acceleration libraries, physically principled simulation content, and AI models into their software frameworks and robot models to enhance efficiency in factories, warehouses, and distribution centers. This enables human colleagues to work in safer environments and serves as intelligent assistants in executing repetitive or ultra-precise tasks.

3. NVIDIA introduces NVIDIA IGX with Holoscan support, enabling enterprise software to run medical, industrial, and scientific artificial intelligence applications in real-time at the edge: To meet the growing demand for real-time artificial intelligence computing technology at the industrial edge, NVIDIA announces the comprehensive launch of NVIDIA AI Enterprise-IGX software with Holoscan on the NVIDIA IGX platform.

• Consumer Devices

1. NVIDIA utilizes GeForce RTX AI PC to deliver the real AI assistant experience: NVIDIA announces the launch of the new NVIDIA RTX technology, designed to support AI assistants and digital human platforms running on new GeForce RTX AI laptops.

2. NVIDIA introduces Digital Human Microservices to lay the foundation for future generative AI digital avatars: NVIDIA announces the comprehensive rollout of NVIDIA ACE generative artificial intelligence microservices to accelerate the development of the next wave of digital humans and numerous breakthroughs in generative AI soon to be introduced on the platform.

Companies in customer service, gaming, and healthcare sectors are among the first to adopt ACE technology, making it easier to create, personalize, and interact with realistic digital humans. These microservices have broad applications in customer service, telehealth, gaming, and entertainment.

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• [News] NVIDIA CEO Jensen Huang Announces the Latest Rubin Architecture – Rubin Ultra GPU to Feature 12 HBM4
• [News] Dell Leak Reveals NVIDIA’s Potential B200 Launch Next Year

(Photo credit: NVIDIA)

NVIDIA CEO Jensen Huang delivered a keynote speech at the NTU (National Taiwan University) Sports Center on June 2. As per a report from TechNews, during the speech, he unveiled the new generation Rubin architecture, showcasing NVIDIA’s accelerated rollout of new architectures, which became the highlight of the evening.

While discussing NVIDIA’s next-generation architecture, Huang mentioned the Blackwell Ultra GPU and indicated that it may continue to be upgraded. He then revealed that the next-generation architecture following Blackwell will be the Rubin architecture.

The Rubin GPU will feature 8 HBM4, while the Rubin Ultra GPU will come with 12 HBM4 chips, he noted.

The new architecture has been named after American astronomer Vera Rubin, who made significant contributions to our understanding of dark matter in the universe and conducted pioneering work on galaxy rotation rates.

Notably, despite the fact that NVIDIA has just launched the new Blackwell platform, it appears that NVIDIA keeps accelerating its roadmap. According to the latest information announced by Jensen Huang, the Rubin GPU will become part of the R series products and is expected to go into mass production in the fourth quarter of 2025. The Rubin GPU and its corresponding platform are anticipated to be released in 2026, followed by the Ultra version in 2027. NVIDIA also confirmed that the Rubin GPU will use HBM4.

Per a report from global media outlet Wccftech, NVIDIA’s Rubin GPU is expected to adopt a 4x reticle design and utilize TSMC’s CoWoS-L packaging technology, along with the N3 process. Moreover, NVIDIA will use next-generation HBM4 DRAM to power its Rubin GPU.

According to Wccftech, currently, NVIDIA employs the fastest HBM3e in its B100 GPU, and it plans to update these chips with the HBM4 version when HBM4 solutions are produced in large quantities by the end of 2025.

Read more

• [News] Dell Leak Reveals NVIDIA’s Potential B200 Launch Next Year
• [News] TSMC’s Advanced Packaging Capacity Fully Booked by NVIDIA and AMD Through Next Year

(Photo credit: NVIDIA)