In DeepSeek Era, Nvidia Fixes On Blackwell Ultra’s AI Money-Making Potential

Revealed at its GTC 2025 event, Nvidia says that its next-generation Blackwell Ultra GPU for AI data centers is designed for reasoning models like DeepSeek R1 and claims that the chip can significantly increase the revenue AI providers generate.

Nvidia has revealed the first details of the successor to its fast-selling Blackwell GPU architecture, saying the follow-up is built for AI reasoning models like DeepSeek R1 while claiming that the GPU can significantly increase the revenue AI providers generate.

Called Blackwell Ultra, the GPU increases the maximum HBM3e high-bandwidth memory by 50 percent to 288 GB and boosts 4-bit floating point (FP4) inference performance by just as much, Nvidia announced Tuesday at its GTC 2025 event alongside new DGX SuperPods, a new DGX Station and new Blackwell-based RTX Pro GPUs.

The company said Blackwell Ultra-based products from technology partners are set to debut in the second half of 2025. These partners include OEMs such as Dell Technologies, Cisco, Hewlett Packard Enterprise, Lenovo and Supermicro as well as cloud service providers like Amazon Web Services, Google Cloud, Microsoft Azure and Oracle Cloud Infrastructure.

In a briefing with journalists the day before, Nvidia executive Ian Buck provided these details and added that Blackwell Ultra is “built for the age of reasoning,” referencing the advent of reasoning models such as the Chinese-developed DeepSeek R1.

While the arrival of DeepSeek R1 and its cost-effective nature earlier this year put into question the need for large data centers filled with Nvidia’s power-hungry and powerful GPUs, the AI computing giant has pushed back on any negative implications by arguing that such breakthroughs point to the need for faster AI chips in greater numbers.

“While DeepSeek can be served with upwards of 1 million tokens per dollar, typically they’ll generate up to 10,000 or more tokens to come up with that answer. This new world of reasoning requires new software, new hardware to help accelerate and advance AI,” said Buck, whose title is vice president of hyperscale and high-performance computing.

With data centers running DeepSeek and other kinds of AI models representing what Buck called a $1 trillion opportunity, Nvidia is focusing on how its GPUs, systems and software can help AI application providers make more money, with Buck saying that Blackwell Ultra alone can enable a 50-fold increase in “data center revenue opportunity.”

The 50-fold increase is based on the performance improvement Buck said Nvidia can provide for the 671-billion-parameter DeepSeek-R1 reasoning model with the new GB300 NVL72 rack-scale platform—which updates the recently launched GB200 NVL72 with the new Blackwell Ultra-based GB300 superchip—over an HGX H100-based data center at the same power level.

Whereas the HGX H100 can deliver 100 tokens per second in 90 seconds with the DeepSeek-R1 model, the GB300 NVL72 can increase the tokens per second by 10 times to 1,000 while shortening the delivery time to just 10 seconds, according to Buck.

“The combination of total token volume [and] dollar per token expands from Hopper to Blackwell by 50X by providing a higher-value service, which offers a premium experience and a different price point in the market,” he said.

“As we reduce the cost of serving these models, they can serve more with the same infrastructure and increase total volume at the same time,” Buck added.

The company did not discuss how much more potential revenue Blackwell Ultra can generate than Blackwell, which became Nvidia’s “fastest product ramp” yet by generating $11 billion from initial shipments between November and January.

Nvidia unveiled Blackwell Ultra as the AI computing giant seeks to not only maintain its dominance but also ensure there continues to be high demand for its products that allowed it to more than double revenue to $130.5 billion last year.

GB300 NVL72 Details, New DGX SuperPods

With the new, Blackwell Ultra-based GB300 NVL72 platform, the company improved its energy efficiency and serviceability, according to Buck.

Consisting of 72 Blackwell Ultra GPUs and 36 Grace CPUs, the GB300 NVL72 platform can achieve 1.1 exaflops of FP4 dense computation, and it comes with 20 TB of high-bandwidth memory as well as 40 TB of fast memory. The platform’s NVLink bandwidth can top out at 130 TBps while networking speeds reach 14.4 TBps.

Nvidia said GB300 NVL72 will be made available on its DGX Cloud AI supercomputing platform, which is accessible from cloud service providers like AWS, Microsoft Azure and Google Cloud.

With Blackwell Ultra, Nvidia will provide two flavors of new DGX SuperPod configurations. The liquid-cooled DGX SuperPod with DGX GB300 systems consists of eight GB300 NVL72 platforms, amounting to 288 Grace CPUs, 576 Blackwell Ultra GPUs and 300 TB of fast memory that can produce 11.4 exaflops of FP4 computation.

The DGX SuperPod with DGX B300 systems, on the other hand, is pitched by Nvidia as a “scalable, air-cooled architecture” that will be offered as a new design for the company’s modular MGX server racks and enterprise data centers.

These B300-based DGX SuperPod clusters are made up of Nvidia’s HGX B300 NVL16 platform, which the company said provides 11 times faster inference on large language models, seven times more compute and four times larger memory compared to a Hopper-based platform.

Nvidia did not disclose power requirements in the Monday briefing.

Blackwell Ultra-Based DGX Station, RTX Pro Blackwell GPUs

Nvidia also revealed a new Blackwell Ultra-powered DGX Station desktop PC as well as new Blackwell-based RTX Pro GPUs for laptops, desktops and servers. It also provided new details for the Project Digits’ mini PC that was revealed at CES 2025 in January.

The company called the DGX Station the “ultimate desktop computer for the AI era” because of how it features a GB300 Grace Blackwell Ultra Desktop Superchip and 784 GB of unified system memory to enable 20 petaflops of AI performance.

The DGX Station will also feature the Nvidia ConnectX-8 SuperNIC, which enables networking speeds of up to 800 Gbps for connecting multiple DGX Stations.

Nvidia said the DGX Station will be made available from several OEMs, including Dell, HP Inc. and Supermicro, later this year.

Nvidia revealed that Project Digits is now known as DGX Spark, which will feature the GB10 Grace Blackwell Superchip to deliver up to 1,000 trillion operations per second of AI computation for the fine-tuning and inferencing of reasoning models.

Asus, Dell, HP and Lenovo plan to release their own version of the DGX Spark. While Nvidia didn’t indicate a release window, it said its website is accepting reservations now.

Nvidia said the RTX Pro Blackwell GPUs will feature “groundbreaking AI and graphics performance,” which will “redefine visualization, simulation and scientific computing for millions of professions,” according to Nvidia.

Compared with the Ada Lovelace-based RTX Pro GPUs, the new Blackwell models come with an improved streaming multiprocessor that delivers 50 percent faster throughput and new neutral shaders that “integrate AI inside of programmable shaders” for AI-augmented graphics.

They also sport fourth-generation RT Cores that can deliver up to double the ray tracing performance, fifth-generation Tensor Cores that enable up to 4,000 AI trillion operations per second and add support for FP4 precision as well as larger, faster GDDR7 memory.

The RTX Pro GPUs for laptops, spanning from the high-end 5000 series to the low-end 500 series, will support up to 24 GB of GDDR7 memory with error-correction while the desktop models, spanning from the 5000 series to the 4000 series, will max out to 96 GB. The RTX Pro 6000 series for data centers will also top out to 96 GB.

Nvidia said the RTX Pro 6000 data center GPU will be made available soon in server configurations from OEMs such as Cisco Systems, Dell, Hewlett Packard Enterprise and Lenovo. The GPU will become available in instances from Amazon Web Services, Google Cloud, Microsoft Azure and CoreWeave later this year.

The RTX Pro desktop GPUs, on the other hand, are expected to debut in April with availability from distributors PNY and TD Synnex. They will then arrive in PCs the following month from OEMs and system builders like Boxx, Dell, HP, Lambda and Lenovo.

The RTX Pro laptops GPUs will land later this year from Dell, HP, Lenovo and Razer.