Deploy Blackwell GPU infrastructure with NVIDIA® B200 SXM6, AMD Turin CPUs and up to 1,536 GB of VRAM, with a DGX B200 pre-release option.
NVIDIA DGX B200 is designed for AI workloads that need large VRAM, high-speed GPU interconnect and consistent compute capacity for training, fine-tuning or inference on large models.
This page lists every DGX B200 configuration with its specifications and billing terms.
Blackwell GPU infrastructure for AI training, fine-tuning, inference and HPC workloads needing large VRAM.
B200 SXM6 options at 180 GB/192 GB, scaling from a single GPU to a full 8-GPU node.
High-core-count AMD Turin CPUs accelerate data pipelines, preprocessing and parallel compute workloads.
Supports NVLink/P2P at 1.8 TB/s or 900 GB/s depending on configuration, for multi-GPU workloads.
NVIDIA® B200 SXM6
NVIDIA® B200 SXM6
NVIDIA® B200 SXM6
B200 SXM6 192 GB
B200 SXM6 180 GB
B200 SXM6 180 GB
B200 SXM6 180 GB
B200 configurations scale GPU capacity across every stage: experimentation, fine-tuning, training, and production inference.
Suited to LLMs, computer vision, multimodal AI and models with large VRAM requirements.
Speeds up deployment of chatbots, RAG, embeddings, recommendation and AI applications in production.
1x, 2x, 4x and 8x GPU options let you scale resources as your project develops.
Plans offer 6,000 GB to 22,528 GB of storage capacity, suited to datasets, checkpoints, and model artifacts.
Available on 1, 3, 6, 12, 24, 36, 48, and 60-month terms.
HiTechCloud helps you choose the configuration, drivers, frameworks and runtime, and run the AI workload.
Use DGX B200 for fine-tuning, instruction tuning, model evaluation and enterprise GenAI pipelines.
Serves AI models at low latency, with large VRAM and multi-GPU scaling.
Accelerate simulation, data analysis, rendering, scientific research, and GPU-intensive workloads.
Powerful capacity, optimized to accelerate AI/ML and high-performance workloads at any scale.
Training, inference, or fine-tuning - HiTechCloud offers a range of GPUs to match your needs, with transparent pricing and on-demand deployment environments.
HiTechCloud GPU instances combine NVLink/PCIe, InfiniBand (RDMA), and RAIL topology to optimize AI/HPC performance.
A network and GPU fabric designed so AI workloads scale reliably, easing bandwidth bottlenecks and holding performance at scale.
High-speed GPU-to-GPU connectivity within and between nodes, reducing bottlenecks during model training.
Low-latency connectivity optimized for distributed training and reduced processing load on the host.
A parallel network architecture delivering higher bandwidth, redundancy, and consistent performance at any scale.
From a single GPU to large clusters, HiTechCloud provisions resources ahead of demand and gets the most out of every instance.
Scale GPU resources automatically from a handful to thousands of GPUs, with forecasting and provisioning ahead of demand.
Access over SSH, TCP, and HTTP with built-in protection layers that keep enterprise data safe and access fully controlled.
Partition a single GPU into multiple independent instances to run AI workloads in parallel, improving utilization and lowering infrastructure cost.
From large-scale training to real-time inference - pay only when you actually run, on a GPU cloud platform built for every AI and high-performance workload.
From sign-up to a running GPU instance in under 5 minutes - no complex setup, no resource reservations, no charges while idle. Just deploy, run, and pay only for what you use.
A complete management platform for deploying and operating AI agents securely at scale on enterprise-grade infrastructure.
Explore AgentBaseA unified platform for training, fine-tuning, and deploying AI models at any scale.
Explore AI PlatformSupports fast search, real-time analytics, log and large-scale event data, and vector databases for RAG.
Explore Vector DatabaseManaged Kubernetes for container orchestration, AI services, and GPU cloud workloads.
Explore KubernetesDeploy systems and applications closer to your users, reducing latency and meeting local regulatory requirements.
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Large enterprises and fast-growing startups choose HiTechCloud for secure, high-performance AI cloud solutions that let them innovate and scale.
The HiTechCloud team advises on GPU architecture, networking, security, and an operating model matched to your real workloads.
Quick facts before choosing the NVIDIA DGX B200 at HiTechCloud.
Suited to AI training, fine-tuning, inference, HPC, simulation, data science, and workloads that need large VRAM.
Suited to businesses building an AI factory, training large models, running inference at scale, or needing a powerful GPU cloud platform.
Choose it when the workload needs current-generation performance, large VRAM, multiple GPUs, and room to scale for enterprise training or inference.
Yes. The DGX B200 suits fine-tuning, pre-training, RAG pipelines, model serving and large-scale AI data processing.
Yes. HiTechCloud advises on GPU count, storage, network, runtime, framework and an operating approach based on project requirements.
Establish your model size, dataset, batch size, framework, run time and security requirements to choose the right configuration.
Plans are available on 1, 3, 6, 12, 24, 36, 48, and 60-month terms.
HiTechCloud helps you select the GPU count, VRAM, CPU cores, storage, runtime, and a GPU cloud operating model that fits.
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