NVIDIA's supply of Chinese market-exclusive H20 AI GPU faces an uncertain future, due to recently introduced energy-efficiency guidelines. As covered over a year ago, Team Green readied a regional alternative to its "full fat" H800 "Hopper" AI GPU—designed and/or neutered to comply with US sanctions. Despite being less performant than Western siblings, the H20 model proved to be highly popular by mid-2024—industry analysis projected "$12 billion in take-home revenue" for NVIDIA. According to a fresh Reuters news piece, demand for cut-down "Hopper" hardware has surged throughout early 2025. The report cites "a rush to adopt Chinese AI startup DeepSeek's cost-effective AI models" as the main cause behind an increased snap up rate of H20 chips; with the nation's "big three" AI players—Tencent, Alibaba and ByteDance—driving the majority of sales.

The supply of H20 AI GPUs seems to be under threat on several fronts; Reuters points out that "U.S. officials were considering curbs on sales of H20 chips to China" back in January. Returning to the present day, their report sources "unofficial" statements from H3C—one of China's largest server equipment manufacturers and a key OEM partner for NVIDIA. An anonymous company insider outlined a murky outlook: "H20's international supply chain faces significant uncertainties...We were told the chips would be available, but when it came time to actually purchase them, we were informed they had already been sold at higher prices." More (rumored) bad news has arrived in the shape of alleged Chinese government intervention—the Financial Times posits that local regulators have privately advised that Tencent, Alibaba and ByteDance not purchase NVIDIA H20 chips.

Today, at NVIDIA GTC, Lenovo unveiled new Lenovo Hybrid AI Advantage with NVIDIA solutions designed to accelerate AI adoption and boost business productivity by fast-tracking agentic AI that can reason, plan and take action to reach goals faster. The validated, full-stack AI solutions enable enterprises to quickly build and deploy AI agents for a broad range of high-demand use cases, increasing productivity, agility and trust while accelerating the next wave of AI reasoning for the new era of agentic AI.

New global IDC research commissioned by Lenovo reveals that ROI remains the greatest AI adoption barrier, despite a three-fold spend increase. AI agents are revolutionizing enterprise workflows and lowering barriers to ROI by supporting employees with complex problem-solving, coding, and multistep planning that drives speed, innovation and productivity. As CIOs and business leaders seek tangible return on AI investment, Lenovo is delivering hybrid AI solutions that unleash and customize agentic AI at every scale.

Supermicro, Inc., a Total IT Solution Provider for AI/ML, HPC, Cloud, Storage, and 5G/Edge, today announced support for the new NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs on a range of workload-optimized GPU servers and workstations. Specifically optimized for the NVIDIA Blackwell generation of PCIe GPUs, the broad range of Supermicro servers will enable more enterprises to leverage accelerated computing for LLM-inference and fine-tuning, agentic AI, visualization, graphics & rendering, and virtualization. Many Supermicro GPU-optimized systems are NVIDIA Certified, guaranteeing compatibility and support for NVIDIA AI Enterprise to simplify the process of developing and deploying production AI.

"Supermicro leads the industry with its broad portfolio of application optimized GPU servers that can be deployed in a wide range of enterprise environments with very short lead times," said Charles Liang, president and CEO of Supermicro. "Our support for the NVIDIA RTX PRO 6000 Blackwell Server Edition GPU adds yet another dimension of performance and flexibility for customers looking to deploy the latest in accelerated computing capabilities from the data center to the intelligent edge. Supermicro's broad range of PCIe GPU-optimized products also support NVIDIA H200 NVL in 2-way and 4-way NVIDIA NVLink configurations to maximize inference performance for today's state-of-the-art AI models, as well as accelerating HPC workloads."

Marking one year since the launch of the Dell AI Factory with NVIDIA, Dell Technologies (NYSE: DELL) announces new AI PCs, infrastructure, software and services advancements to accelerate enterprise AI innovation at any scale. Successful AI deployments are vital for enterprises to remain competitive, but challenges like system integration and skill gaps can delay the value enterprises realize from AI. More than 75% of organizations want their infrastructure providers to deliver capabilities across all aspects of the AI adoption journey, driving customer demand for simplified AI deployments that can scale.

As the top provider of AI centric infrastructure, Dell Technologies - in collaboration with NVIDIA - provides a consistent experience across AI infrastructure, software and services, offering customers a one-stop shop to scale AI initiatives from deskside to large-scale data center deployments.

TrendForce reveals that the combined revenue of the world's top 10 IC design houses reached approximately US$249.8 billion in 2024, marking a 49% YoY increase. The booming AI industry has fueled growth across the semiconductor sector, with NVIDIA leading the charge, posting an astonishing 125% revenue growth, widening its lead over competitors, and solidifying its dominance in the IC industry.

Looking ahead to 2025, advancements in semiconductor manufacturing will further enhance AI computing power, with LLMs continuing to emerge. Open-source models like DeepSeek could lower AI adoption costs, accelerating AI penetration from servers to personal devices. This shift positions edge AI devices as the next major growth driver for the semiconductor industry.

Today, Bloomberg reported that the US government under Trump administration is probing whether Chinese AI company DeepSeek circumvented export restrictions to acquire advanced NVIDIA GPUs through Singaporean intermediaries. The investigation follows concerns that DeepSeek's AI model, R1—reportedly rivaling leading systems from OpenAI and Google—may have been trained using restricted hardware that is blocked from exporting to China. Singapore's role in NVIDIA's global sales has surged, with the nation accounting for 22% of the chipmaker's revenue in Q3 FY2025, up from 9% in Q3 FY2023. This spike coincides with tightened US export controls on AI chips to China, prompting speculation that Singapore serves as a pipe for Chinese firms to access high-end GPUs like the H100, which cannot be sold directly to China.

DeepSeek has not disclosed hardware details for R1 but revealed its earlier V3 model was trained using 2,048 H800 GPUs (2.8 million GPU hours), achieving efficiency surpassing Meta's Llama 3, which required 30.8 million GPU hours. Analysts suggest R1's performance implies even more powerful infrastructure, potentially involving restricted chips. US authorities, including the White House and FBI, are examining whether third parties in Singapore facilitated the transfer of controlled GPUs to DeepSeek. A well-known semiconductor analyst firm, SemiAnalysis, believes that DeepSeek acquired around 50,000 NVIDIA Hopper GPUs, which includes a mix of H100, H800, and H20. NVIDIA clarified that its reported Singapore revenue reflects "bill to" customer locations, not final destinations, stating most products are routed to the US or Western markets.

Despite recent rumors speculating on NVIDIA's supposed cancellation of the B100 in favor of the B200A, TrendForce reports that NVIDIA is still on track to launch both the B100 and B200 in the 2H24 as it aims to target CSP customers. Additionally, a scaled-down B200A is planned for other enterprise clients, focusing on edge AI applications.

TrendForce reports that NVIDIA will prioritize the B100 and B200 for CSP customers with higher demand due to the tight production capacity of CoWoS-L. Shipments are expected to commence after 3Q24. In light of yield and mass production challenges with CoWoS-L, NVIDIA is also planning the B200A for other enterprise clients, utilizing CoWoS-S packaging technology.

When NVIDIA started preparing the H20 GPU for China, the company anticipated great demand from sanction-obeying GPUs. However, we now know precisely what the company makes from its Chinese venture: an astonishing $12 billion in take-home revenue. Due to the massive demand for NVIDIA GPUs, Chinese AI research labs are acquiring as many as they can get their hands on. According to a report from Financial Times, citing SemiAnalysis as its source, NVIDIA will sell over one million H20 GPUs in China. This number far outweighs the number of home-grown Huawei Ascend 910B accelerators that the Chinese companies plan to source, with numbers being "only" 550,000 Ascend 910B chips. While we don't know if Chinese semiconductor makers like SMIC are capable of producing more chips or if the demand isn't as high, we know why NVIDIA H20 chips are the primary target.

The Huawei Ascend 910B features Total Processing Performance (TPP), a metric developed by US Govt. to track GPU performance measuring TeraFLOPS times bit-length of over 5,000, while the NVIDIA H20 comes to 2,368 TPP, which is half of the Huawei accelerator. That is the performance on paper, where SemiAnalysis notes that the real-world performance is actually ahead for the H20 GPU due to better memory configuration of the GPU, including higher HBM3 memory bandwidth. All of this proves to be a better alternative than Ascend 910B accelerator, accounting for an estimate of over one million GPUs shipped this year in China. With an average price of $12,000 per NVIDIA H20 GPU, China's $12 billion revenue will undoubtedly help raise NVIDIA's 2024 profits even further.

TrendForce reports that NVIDIA's Hopper H100 began to see a reduction in shortages in 1Q24. The new H200 from the same platform is expected to gradually ramp in Q2, with the Blackwell platform entering the market in Q3 and expanding to data center customers in Q4. However, this year will still primarily focus on the Hopper platform, which includes the H100 and H200 product lines. The Blackwell platform—based on how far supply chain integration has progressed—is expected to start ramping up in Q4, accounting for less than 10% of the total high-end GPU market.

The die size of Blackwell platform chips like the B100 is twice that of the H100. As Blackwell becomes mainstream in 2025, the total capacity of TSMC's CoWoS is projected to grow by 150% in 2024 and by over 70% in 2025, with NVIDIA's demand occupying nearly half of this capacity. For HBM, the NVIDIA GPU platform's evolution sees the H100 primarily using 80 GB of HBM3, while the 2025 B200 will feature 288 GB of HBM3e—a 3-4 fold increase in capacity per chip. The three major manufacturers' expansion plans indicate that HBM production volume will likely double by 2025.

Driving a fundamental shift in the high-performance computing industry toward AI-powered systems, NVIDIA today announced nine new supercomputers worldwide are using NVIDIA Grace Hopper Superchips to speed scientific research and discovery. Combined, the systems deliver 200 exaflops, or 200 quintillion calculations per second, of energy-efficient AI processing power.

New Grace Hopper-based supercomputers coming online include EXA1-HE, in France, from CEA and Eviden; Helios at Academic Computer Centre Cyfronet, in Poland, from Hewlett Packard Enterprise (HPE); Alps at the Swiss National Supercomputing Centre, from HPE; JUPITER at the Jülich Supercomputing Centre, in Germany; DeltaAI at the National Center for Supercomputing Applications at the University of Illinois Urbana-Champaign; and Miyabi at Japan's Joint Center for Advanced High Performance Computing - established between the Center for Computational Sciences at the University of Tsukuba and the Information Technology Center at the University of Tokyo.

NVIDIA today announced that it will accelerate quantum computing efforts at national supercomputing centers around the world with the open-source NVIDIA CUDA-Q platform. Supercomputing sites in Germany, Japan and Poland will use the platform to power the quantum processing units (QPUs) inside their NVIDIA-accelerated high-performance computing systems.

QPUs are the brains of quantum computers that use the behavior of particles like electrons or photons to calculate differently than traditional processors, with the potential to make certain types of calculations faster. Germany's Jülich Supercomputing Centre (JSC) at Forschungszentrum Jülich is installing a QPU built by IQM Quantum Computers as a complement to its JUPITER supercomputer, supercharged by the NVIDIA GH200 Grace Hopper Superchip. The ABCI-Q supercomputer, located at the National Institute of Advanced Industrial Science and Technology (AIST) in Japan, is designed to advance the nation's quantum computing initiative. Powered by the NVIDIA Hopper architecture, the system will add a QPU from QuEra. Poland's Poznan Supercomputing and Networking Center (PSNC) has recently installed two photonic QPUs, built by ORCA Computing, connected to a new supercomputer partition accelerated by NVIDIA Hopper.

NVIDIA's next-gen Blackwell platform, which includes B-series GPUs and integrates NVIDIA's own Grace Arm CPU in models such as the GB200, represents a significant development. TrendForce points out that the GB200 and its predecessor, the GH200, both feature a combined CPU+GPU solution, primarily equipped with the NVIDIA Grace CPU and H200 GPU. However, the GH200 accounted for only approximately 5% of NVIDIA's high-end GPU shipments. The supply chain has high expectations for the GB200, with projections suggesting that its shipments could exceed millions of units by 2025, potentially making up nearly 40 to 50% of NVIDIA's high-end GPU market.

Although NVIDIA plans to launch products such as the GB200 and B100 in the second half of this year, upstream wafer packaging will need to adopt more complex and high-precision CoWoS-L technology, making the validation and testing process time-consuming. Additionally, more time will be required to optimize the B-series for AI server systems in aspects such as network communication and cooling performance. It is anticipated that the GB200 and B100 products will not see significant production volumes until 4Q24 or 1Q25.

NVIDIA today announced that Australia's Pawsey Supercomputing Research Centre will add the NVIDIA CUDA Quantum platform accelerated by NVIDIA Grace Hopper Superchips to its National Supercomputing and Quantum Computing Innovation Hub, furthering its work driving breakthroughs in quantum computing.

Researchers at the Perth-based center will leverage CUDA Quantum - an open-source hybrid quantum computing platform that features powerful simulation tools, and capabilities to program hybrid CPU, GPU and QPU systems - as well as, the NVIDIA cuQuantum software development kit of optimized libraries and tools for accelerating quantum computing workflows. The NVIDIA Grace Hopper Superchip - which combines the NVIDIA Grace CPU and Hopper GPU architectures - provides extreme performance to run high-fidelity and scalable quantum simulations on accelerators and seamlessly interface with future quantum hardware infrastructure.

NVIDIA's H800 AI GPU was rolled out last year to appease the Sanction Gods—but later on, the US Government deemed the cutdown "Hopper" part to be far too potent for Team Green's Chinese enterprise customers. Last October, newly amended export conditions banned sales of the H800, as well as the slightly older (plus similarly gimped) A800 "Ampere" GPU in the region. NVIDIA's engineering team returned to the drawing board, and developed a new range of compliantly weakened products. An exclusive Reuters report suggests that Team Green is taking pre-orders for a refreshed "Hopper" GPU—the latest China-specific flagship is called "HGX H20." NVIDIA web presences have not been updated with this new model, as well as Ada Lovelace-based L20 PCIe and L2 PCIe GPUs. Huawei's competing Ascend 910B is said to be slightly more performant in "some areas"—when compared to the H20—according to insiders within the distribution network.

The leakers reckon that NVIDIA's mainland distributors will be selling H20 models within a price range of $12,000 - $15,000—Huawei's locally developed Ascend 910B is priced at 120,000 RMB (~$16,900). One Reuters source stated that: "some distributors have started advertising the (NVIDIA H20) chips with a significant markup to the lower end of that range at about 110,000 yuan ($15,320). The report suggests that NVIDIA refused to comment on this situation. Another insider claimed that: "distributors are offering H20 servers, which are pre-configured with eight of the AI chips, for 1.4 million yuan. By comparison, servers that used eight of the H800 chips were sold at around 2 million yuan when they were launched a year ago." Small batches of H20 products are expected to reach important clients within the first quarter of 2024, followed by a wider release in Q2. It is believed that mass production will begin around Spring time.