NVIDIA® B300 SXM6 GPU Cloud

NVIDIA® B300 SXM6 for new-generation AI training, inference and HPC

High-performance GPU infrastructure with NVIDIA® B300 SXM6 262 GB, AMD EPYC Turin CPUs, up to 2,304 GB of VRAM and 1.8 TB/s NVLink/peer-to-peer interconnect for large-scale AI workloads.

1–8 GPU 288–2304 GB VRAM AMD EPYC Turin 6000 GB Disk
Blackwell GPU Platform

Cloud GPU for ever-larger AI models

The NVIDIA® B300 SXM6 is built for workloads that need GPU compute power, large VRAM and high-speed multi-GPU interconnect. Configurations from 1 to 8 GPUs let a business scale to match demand.

The available packages are 1B300.30V, 2B300.60V, 4B300.120V and 8B300.240V, with AMD EPYC Turin CPUs, large memory, 6,000 GB of disk and a full range of billing cycles.

01

NVIDIA® B300 SXM6

Current-generation GPUs for AI training, inference, HPC, simulation and large-scale data processing with very large VRAM.

02

AMD EPYC Turin

AMD EPYC Turin CPUs with high core counts help balance AI pipelines, preprocessing, data loaders and parallel compute workloads.

03

Up to 2,304 GB VRAM

From 1 to 8 GPUs and 288 GB to 2,304 GB of VRAM for large models, large batches and multi-GPU workloads.

04

NVLink/P2P 1,8 TB/s

High-speed GPU interconnect enables fast GPU-to-GPU data exchange for distributed training and high-performance inference.

NVIDIA® B300 SXM6 pricing

Choose a GPU configuration by AI workload scale

3201

1B300.30V

B300 SXM6 262 GB

198,569,880 VND / 1 month
  • GPU1 GPU
  • CPUAMD EPYC Turin
  • Core30 Core
  • RAM275 GB RAM
  • VRAM288 GB VRAM
  • NVLink/P2PNVLink 1,8 TB/s
  • Disk6000 GB
Sign up now
3203

4B300.120V

B300 SXM6 262 GB

646,030,080 VND / 1 month
  • GPU4 GPU
  • CPUAMD EPYC Turin
  • Core120 Core
  • RAM1100 GB RAM
  • VRAM1152 GB VRAM
  • NVLink/P2PP2P 1,8 TB/s
  • Disk6000 GB
Sign up now
3204

8B300.240V

B300 SXM6 262 GB

1,242,643,680 VND / 1 month
  • GPU8 GPU
  • CPUAMD EPYC Turin
  • Core240 Core
  • RAM2200 GB RAM
  • VRAM2304 GB VRAM
  • NVLink/P2PP2P 1,8 TB/s
  • Disk6000 GB
Sign up now
GPU Infrastructure

Optimized for AI, HPC, and compute-intensive workloads

NVIDIA® B300 SXM6 scales from a single GPU to a multi-GPU node, covering each stage of AI product development.

Optimized for AI training

Suited to LLM training, computer vision, recommendation, speech AI and multimodal models that need large GPU memory.

Large-scale inference

Accelerate AI model serving for production applications, chatbots, embeddings, RAG and enterprise AI systems.

HPC & Simulation

Handles scientific computing, engineering simulation, data analysis, and high-performance rendering workloads.

Multi-GPU configurations

A choice of 1, 2, 4 or 8 GPUs lets you scale with each stage of model development and your compute needs.

Large disk capacity

Every plan includes 6,000 GB of disk, suited to storing datasets, checkpoints, model artifacts and AI development environments.

Deployment support

HiTechCloud advises on configuration selection, runtime environment, drivers, frameworks and running GPU workloads.

Use cases

Deployment scenarios suited to the NVIDIA® B300 SXM6

LLM Training & fine-tuning large models

B300 SXM6 clusters for pre-training, fine-tuning, alignment, and evaluation of language or multimodal models.

AI App Enterprise AI inference

Run inference for chatbots, image analysis, speech, recommendation and internal AI platforms.

Research HPC, simulation and R&D

Accelerate research, simulation, scientific computing, rendering and large-volume data processing.

01

High-performance GPU instances for a wide range of workloads

Powerful capacity, optimized to accelerate AI/ML and high-performance workloads at any scale.

02

A broad range of infrastructure options

Training, inference, or fine-tuning - HiTechCloud offers a range of GPUs to match your needs, with transparent pricing and on-demand deployment environments.

03

Built to NVIDIA reference architecture

HiTechCloud GPU instances combine NVLink/PCIe, InfiniBand (RDMA), and RAIL topology to optimize AI/HPC performance.

GPU cloud architecture

Three core connectivity layers for high-performance GPU clusters

A network and GPU fabric designed so AI workloads scale reliably, easing bandwidth bottlenecks and holding performance at scale.

NVLink and PCIe Switch for HiTechCloud GPU instances

NVLink / PCIe Switch

High-speed GPU-to-GPU connectivity within and between nodes, reducing bottlenecks during model training.

InfiniBand RDMA for distributed training

InfiniBand (RDMA)

Low-latency connectivity optimized for distributed training and reduced processing load on the host.

RAIL topology for high-performance GPU clusters

RAIL Topology

A parallel network architecture delivering higher bandwidth, redundancy, and consistent performance at any scale.

Auto scaling

GPU auto scaling and utilization optimization

From a single GPU to large clusters, HiTechCloud provisions resources ahead of demand and gets the most out of every instance.

GPU auto scaling with Kubernetes

Auto scaling with Kubernetes

Scale GPU resources automatically from a handful to thousands of GPUs, with forecasting and provisioning ahead of demand.

SSH, TCP, and HTTP connection security for GPU instances

Security for every access connection

Access over SSH, TCP, and HTTP with built-in protection layers that keep enterprise data safe and access fully controlled.

Optimize GPU utilization with MIG

Optimize GPU utilization with MIG

Partition a single GPU into multiple independent instances to run AI workloads in parallel, improving utilization and lowering infrastructure cost.

GPU instance

Transparent pricing, no hidden fees

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.

Ready to launch your first GPU instance?

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.

The HiTechCloud ecosystem

More than compute - manage, scale, and build everything on one straightforward cloud ecosystem.

AgentBase

A complete management platform for deploying and operating AI agents securely at scale on enterprise-grade infrastructure.

Explore AgentBase

AI Platform

A unified platform for training, fine-tuning, and deploying AI models at any scale.

Explore AI Platform

Vector Database

Supports fast search, real-time analytics, log and large-scale event data, and vector databases for RAG.

Explore Vector Database

Kubernetes

Managed Kubernetes for container orchestration, AI services, and GPU cloud workloads.

Explore Kubernetes
Southeast Asia

Scale with confidence across Southeast Asia

Deploy systems and applications closer to your users, reducing latency and meeting local regulatory requirements.

01

Bangkok

BKK-01

03

Ho Chi Minh

HCM-01 · HCM-02 · HCM-03

02

Ha Noi

HAN-01 · HAN-02

Southeast Asia regional map for HiTechCloud infrastructure
1,000+ businesses

A partner for your digital transformation journey

Large enterprises and fast-growing startups choose HiTechCloud for secure, high-performance AI cloud solutions that let them innovate and scale.

Have a specific requirement? HiTechCloud is ready to help.

The HiTechCloud team advises on GPU architecture, networking, security, and an operating model matched to your real workloads.

FAQ

FAQ

Quick facts before choosing an NVIDIA® B300 SXM6 configuration at HiTechCloud.

Which workloads is the NVIDIA® B300 SXM6 suited to?

Suited to AI training, fine-tuning, inference, HPC, simulation, rendering, large-scale data processing and workloads that need large VRAM.

Should I choose one GPU or several?

1 GPU suits experimentation or small workloads. 2, 4 and 8 GPUs suit large models, distributed training, high-load inference or pipelines that need to scale.

Which CPUs do the plans use?

Every plan uses AMD EPYC Turin CPUs, with core count scaling by GPU count.

Is the B300 SXM6 suitable for training large models?

Yes. The B300 SXM6 suits training, LLM fine-tuning, multi-GPU workloads, and AI pipelines that need high bandwidth and large VRAM capacity.

When should you choose the 8-GPU B300 configuration?

The 8-GPU configuration suits large models, distributed training, high-load inference, large batch processing and workloads that scale across a cluster.

Which runtimes does HiTechCloud support deploying?

HiTechCloud advises on CUDA, drivers, container runtimes, PyTorch, TensorFlow, storage, and an operating model that fits your AI objectives.

What billing cycles are available?

Plans are available on 1, 3, 6, 12, 24, 36, 48, and 60-month terms.

GPU Cloud Ready

Need advice on an NVIDIA® B300 SXM6 configuration for your AI workload?

HiTechCloud helps you choose the number of GPUs, VRAM, CPU cores, runtime environment and an operating roadmap that fits your budget.