Technical Specifications
architecture
NVIDIA Blackwell Ultra
gpu memory
288GB HBM3e
memory bandwidth
Up to 8 TB/s
tensor cores
5th Generation
transformer engine
2nd Generation
precision
FP4, FP8, FP16, BF16, TF32, FP32
interconnect
NVLink 5.0
software
CUDA, TensorRT, NCCL, NVIDIA AI Enterprise
virtualization
NVIDIA vGPU Supported
deployment
HGX, DGX, Enterprise AI Servers, GPU Clusters
workloads
Large Language Models, Reasoning AI, Generative AI, AI Training, AI Inference, Deep Learning, Machine Learning, Computer Vision, Healthcare AI, Scientific Computing, Financial Analytics, Recommendation Engines, Digital Twins, AI Factories
Overview
The NVIDIA B300 Tensor Core GPU represents the next evolution of NVIDIA's Blackwell Ultra architecture, delivering breakthrough performance for enterprise AI, generative AI, reasoning models, hyperscale cloud infrastructure, and high-performance computing (HPC). Designed for organizations building AI factories and deploying trillion-parameter language models, the B300 provides significantly higher memory capacity, AI throughput, and inference performance than previous GPU generations. :contentReference[oaicite:0]{index=0}
Powered by the Blackwell Ultra architecture, the NVIDIA B300 integrates 5th Generation Tensor Cores with advanced FP4 acceleration to maximize AI inference efficiency while maintaining exceptional training performance. Its optimized Transformer Engine automatically selects the ideal precision for every workload, enabling faster execution with lower power consumption across enterprise AI applications. :contentReference[oaicite:1]{index=1}
Featuring up to 288GB of HBM3e memory and approximately 8TB/s memory bandwidth, the B300 can process massive AI datasets, extended context windows, multimodal foundation models, and complex scientific simulations without memory bottlenecks. This makes it an ideal accelerator for Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, recommendation engines, computer vision, healthcare AI, financial analytics, robotics, and digital twins. :contentReference[oaicite:2]{index=2}
The next-generation NVLink 5.0 interconnect enables extremely high-speed GPU-to-GPU communication, allowing multiple NVIDIA B300 GPUs to operate as a unified AI platform. Whether deployed in HGX systems, DGX platforms, enterprise GPU clusters, or cloud AI infrastructure, the B300 delivers outstanding scalability for the most demanding AI workloads. :contentReference[oaicite:3]{index=3}
The NVIDIA B300 integrates seamlessly with CUDA, NVIDIA AI Enterprise, TensorRT, NCCL, Triton Inference Server, CUDA-X libraries, Kubernetes, VMware, Red Hat, and major AI development frameworks, simplifying deployment across modern enterprise environments.
GPUWorld supplies genuine NVIDIA B300 GPU servers, custom AI infrastructure, rack integration, liquid or air-cooled deployments, enterprise installation, and complete AI infrastructure consulting to organizations worldwide.
Frequently Asked Questions
What is the NVIDIA B300 GPU used for?
The NVIDIA B300 is designed for enterprise AI, reasoning models, Large Language Models (LLMs), generative AI, deep learning, scientific computing, AI factories, and hyperscale cloud deployments.
How much memory does the NVIDIA B300 have?
The NVIDIA B300 features up to 288GB of HBM3e memory with approximately 8TB/s memory bandwidth, enabling massive AI models and extremely long context windows.
Which architecture powers the NVIDIA B300?
The NVIDIA B300 is built on NVIDIA's Blackwell Ultra architecture with 5th Generation Tensor Cores, FP4 AI acceleration, Transformer Engine technology, and NVLink 5.0 for scalable AI computing.
Can the NVIDIA B300 be used for AI factories and LLMs?
Yes. The NVIDIA B300 is specifically optimized for AI factories, trillion-parameter Large Language Models, reasoning AI, multimodal AI, Retrieval-Augmented Generation (RAG), AI agents, and enterprise-scale inference deployments
Does GPUWorld supply NVIDIA B300 GPU servers?
Yes. GPUWorld provides NVIDIA B300 GPU servers, enterprise AI infrastructure, HGX server deployments, rack integration, AI cluster design, installation, and ongoing support for businesses and research organizations.
