NVIDIA Blackwell Universal Data Center GPU Accelerates Demanding Enterprise Workloads

The first NVIDIA Blackwell-powered data center GPU built for both enterprise AI and visual computing — the NVIDIA RTX PRO 6000 Blackwell Server Edition — is designed to accelerate the most demanding AI and graphics applications for every industry.

Compared to the previous-generation NVIDIA Ada Lovelace architecture L40S GPU, the RTX PRO 6000 Blackwell Server Edition GPU will deliver a multifold increase in performance across a wide array of enterprise workloads — up to 5x higher large language model (LLM) inference throughput for agentic AI applications, nearly 7x faster genomics sequencing, 3.3x speedups for text-to-video generation, nearly 2x faster inference for recommender systems and over 2x speedups for rendering.

It’s part of the NVIDIA RTX PRO Blackwell series of workstation and server GPUs announced today at NVIDIA GTC, the global AI conference taking place through Friday, March 21, in San Jose, California. The RTX PRO lineup includes desktop, laptop and data center GPUs that support AI and creative workloads across industries.

With the RTX PRO 6000 Blackwell Server Edition, enterprises across various sectors — including architecture, automotive, cloud services, financial services, game development, healthcare, manufacturing, media and entertainment and retail — can enable breakthrough performance for workloads such as multimodal generative AI, data analytics, engineering simulation, and visual computing.

Content creation, semiconductor manufacturing and genomics analysis companies are already set to harness its capabilities to accelerate compute-intensive, AI-enabled workflows.

Universal GPU Delivers Powerful Capabilities for AI and Graphics 

The RTX PRO 6000 Blackwell Server Edition packages powerful RTX AI and graphics capabilities in a passively cooled form factor designed to run 24/7 in data center environments. With 96GB of ultrafast GDDR7 memory and support for Multi-Instance GPU, or MIG, each RTX PRO 6000 can be partitioned into as many as four fully isolated instances with 24GB each to run simultaneous AI and graphics workloads.

RTX PRO 6000 is the first universal GPU to enable secure AI with NVIDIA Confidential Computing, which protects AI models and sensitive data from unauthorized access with strong, hardware-based security — providing a physically isolated trusted execution environment to secure the entire workload while data is in use.

To support enterprise-scale deployments, the RTX PRO 6000 can be configured in high-density accelerated computing platforms for distributed inference workloads — or used to deliver virtual workstations with NVIDIA vGPU software to power AI development and graphics-intensive applications.

The RTX PRO 6000 GPU delivers supercharged inferencing performance across a broad range of AI models and accelerates real-time, photorealistic ray tracing of complex virtual environments. It includes the latest Blackwell hardware and software innovations like fifth-generation Tensor Cores, fourth-generation RT Cores, DLSS 4, a fully integrated media pipeline and second-generation Transformer Engine with support for FP4 precision.

Enterprises can run the NVIDIA Omniverse and NVIDIA AI Enterprise platforms at scale on RTX PRO 6000 Blackwell Server Edition GPUs to accelerate the development and deployment of agentic and physical AI applications, such as image and video generation, LLM inference, recommender systems, computer vision, digital twins and robotics simulation.

Accelerated AI Inference and Visual Computing for Any Industry

Black Forest Labs, creator of the popular FLUX image generation AI, aims to develop and optimize state-of-the-art text-to-image models using RTX PRO 6000 Server Edition GPUs.

“With the powerful multimodal inference capabilities of the RTX PRO 6000 Server Edition, our customers will be able to significantly reduce latency for image generation workflows,” said Robin Rombach, CEO of Black Forest Labs. “We anticipate that, with the server edition GPUs’ support for FP4 precision, our Flux models will run faster, enabling interactive, AI-accelerated content creation.”

Cloud graphics company OTOY will optimize its OctaneRender real-time rendering application for NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs.

“The new NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs unlock brand-new workflows that were previously out of reach for 3D content creators,” said Jules Urbach, CEO of OTOY and founder of the Render Network. “With 96 GB of VRAM, the new server-edition GPUs can run complex neural rendering models within OctaneRender’s GPU path-tracer, enabling artists to tap into incredible new features and tools that blend the precision of traditional CGI augmented with frontier generative AI technology.”

Semiconductor equipment manufacturer KLA plans to use the RTX PRO 6000 Blackwell Server Edition to accelerate inference workloads powering the wafer manufacturing process — the creation of thin discs of semiconductor materials that are core to integrated circuits.

KLA and NVIDIA have worked together since 2008 to advance KLA’s physics-based AI with optimized high-performance computing solutions. KLA’s industry-leading inspection and metrology systems capture and process images by running complex AI algorithms at lightning-fast speeds to find the most critical semiconductor defects.

“Based on early results, we expect great performance from the RTX PRO 6000 Blackwell Server Edition,” said Kris Bhaskar, senior fellow and vice president of AI initiatives at KLA. “The increased memory capacity, FP4 reduced precision and new computational capabilities of NVIDIA Blackwell are going to be particularly helpful to KLA and its customers.”

Boosting Genomics and Drug Discovery Workloads

The RTX PRO 6000 Blackwell Server Edition also demonstrates game-changing acceleration for genomic analysis and drug discovery inference workloads, enabled by a new class of dynamic programming instructions.

On a single RTX PRO 6000 Blackwell Server Edition GPU, Fastq2bam and DeepVariant — elements of the NVIDIA Parabricks pipeline for germline analysis — run up to 1.5x faster compared with using an L40S GPU, and 1.75x faster compared with using an NVIDIA H100 GPU.

For Smith-Waterman, a core algorithm used in many sequence alignment and variant calling applications, RTX PRO 6000 Blackwell Server Edition GPUs accelerate throughput up to 6.8x compared with L40S GPUs.

And for OpenFold2, an AI model that predicts protein structures for drug discovery research, RTX PRO 6000 Blackwell Server Edition GPUs boost inference performance by up to 4.8x compared with L40S GPUs.

Genomics company Oxford Nanopore Technologies is collaborating with NVIDIA to bring the latest AI and accelerated computing technologies to its sequencing systems.

“The NVIDIA Blackwell architecture will help us drive the real-time sequencing analysis of anything, by anyone, anywhere,” said Chris Seymour, vice president of advanced platform development at Oxford Nanopore Technologies. “With the RTX PRO 6000 Blackwell Server Edition, we have seen up to a 2x improvement in basecalling speed across our Dorado platform.”

Availability via Global Network of Cloud Providers and System Partners

Platforms featuring the RTX PRO 6000 Blackwell Server Edition will be available from a global ecosystem of partners starting in May.

AWS, Google Cloud, Microsoft Azure, IBM Cloud, CoreWeave, Crusoe, Lambda, Nebius and Vultr will be among the first cloud service providers and GPU cloud providers to offer instances featuring the RTX PRO 6000 Blackwell Server Edition.

Cisco, Dell Technologies, Hewlett Packard Enterprise, Lenovo and Supermicro are expected to deliver a wide range of servers featuring the RTX PRO 6000 Blackwell Server Edition, as are Advantech, Aetina, Aivres, ASRockRack, ASUS, Compal, Foxconn, GIGABYTE, Inventec, MSI, Pegatron, Quanta Cloud Technology (QCT), MiTAC Computing, NationGate, Wistron and Wiwynn.

To learn more about the NVIDIA RTX PRO Blackwell series and other advancements in AI, watch the GTC keynote by NVIDIA founder and CEO Jensen Huang: