Nvidia

The NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition is a high-performance professional graphics card designed for compact workstations requiring substantial computational power within a constrained thermal envelope. Leveraging the NVIDIA Blackwell architecture, this GPU delivers exceptional performance for AI, 3D rendering, and scientific computing applications.

The NVIDIA RTX PRO 5000 Blackwell is a professional-grade graphics card designed for demanding AI, simulation, and visualization workloads. Built on the NVIDIA Blackwell architecture, it offers a significant performance boost over its predecessors.

The NVIDIA RTX PRO 4500 Blackwell is a professional-grade graphics card designed for demanding AI, simulation, and visualization workloads. Built on the NVIDIA Blackwell architecture, it offers a significant performance boost over its predecessors.

The NVIDIA RTX PRO 4000 Blackwell is a high-performance workstation graphics card built on the Blackwell architecture. It is designed for demanding professional workloads such as AI development, simulation, 3D modeling, and high-end visualization. Featuring 8,960 CUDA cores and 280 Tensor Cores, the RTX PRO 4000 provides exceptional parallel processing power for deep learning tasks and rendering. With 24 GB of GDDR7 ECC memory and a 192-bit memory interface, it ensures rapid data handling for large-scale projects.

The NVIDIA RTX PRO 6000 Blackwell Server Edition is engineered for high-performance AI and visual computing in data centers. Built on the advanced NVIDIA Blackwell architecture, it features 24,064 CUDA cores, 752 5th-generation Tensor Cores, and 188 4th-generation RT Cores. Equipped with 96 GB of GDDR7 memory with ECC, it offers exceptional memory bandwidth of up to 1.6 TB/s. The GPU supports PCIe Gen 5 x16 interface, enabling rapid data transfer. Its power consumption ranges from 400W to 600W, configurable based on workload requirements.

The NVIDIA H200 SXM Tensor Core GPU is engineered to accelerate generative AI and high-performance computing (HPC) workloads. Built on the NVIDIA Hopper™ architecture, it features 141 GB of HBM3e memory with a memory bandwidth of 4.8 TB/s, making it the first GPU to offer such high-capacity memory. This substantial memory capacity and bandwidth enable the handling of large-scale AI models and complex HPC simulations with improved efficiency.

The NVIDIA H200 NVL Tensor Core GPU is a high-performance graphics processor designed for data centers, cloud computing, and high-performance computing (HPC) workloads. It is built on the NVIDIA Hopper architecture and equipped with 141 GB of HBM3e memory with a memory bandwidth of 4.8 TB/s. With a maximum thermal design power (TDP) of up to 600 watts, the H200 NVL delivers exceptional performance for tasks requiring intensive computation, such as training and inference for deep learning models, large data processing, and scientific computing.

The NVIDIA H100 SXM Tensor Core GPU is built on the advanced NVIDIA Hopper architecture, utilizing TSMC's 5nm process technology. Designed for high-performance computing and AI workloads, this GPU delivers an exceptional 16,896 CUDA cores and 528 Tensor Cores of the fourth generation, enabling groundbreaking performance in deep learning, machine learning, and scientific simulations. With 80 GB of HBM3 memory and a memory bandwidth of 3.36 TB/s, the H100 ensures efficient data processing and smooth execution of the most demanding tasks. Its high interconnect bandwidth of 900 GB/s, thanks to NVIDIA NVLink, allows for seamless multi-GPU scaling.

The NVIDIA H100 NVL Tensor Core GPU is engineered for high-performance AI inference, particularly excelling in large language model (LLM) applications. Built on the NVIDIA Hopper architecture and fabricated using TSMC's 4N process, it integrates two GH100 GPUs, each equipped with 94 GB of HBM3 memory, totaling 188 GB. This configuration delivers a combined memory bandwidth of 7.8 TB/s, facilitating rapid data processing for complex AI workloads. The GPU supports up to 3,341 TFLOPS of FP8 Tensor Core performance and 835 TFLOPS with TF32 sparsity, ensuring efficient computation for diverse AI models. 

The NVIDIA L4 Tensor Core GPU is a versatile, energy-efficient accelerator designed for AI inference, video processing, and graphics workloads in data centers and edge environments. Built on the Ada Lovelace architecture and fabricated using TSMC's 4N process, the L4 features 7,680 CUDA cores, 240 fourth-generation Tensor Cores, and 60 RT Cores. It comes equipped with 24 GB of GDDR6 memory on a 192-bit interface, delivering a memory bandwidth of 300 GB/s. Operating at a base clock of 795 MHz and boosting up to 2,040 MHz, the L4 achieves peak FP32 performance of 30.3 TFLOPS and FP8 Tensor performance up to 485 TFLOPS with sparsity.