Faster simulation and higher performance per watt.
A program supporting startups with Cloud and AI Factory services at HITECHCLOUD
HiTechCloud Bare Metal GPU
Bare Metal GPU – high performance, optimized cost
Full control over your GPUs, with optimized resource use and lower cost for large-scale AI workloads.
Dedicated GPU
Training & Inference
HPC Performance
24/7 support
Substantially shortens training time for large, complex models.
Very low latency and high throughput for AI applications at real deployment scale.
Bare Metal AI Infrastructure
Dedicated physical GPUs for AI training, inference and HPC needing consistent performance
HiTechCloud Bare Metal GPU provides dedicated GPU resources, giving businesses direct control over the operating system, drivers, frameworks, data and workload scheduling.
The service suits both distributed training and AI inference, with H100, B200, GH200 and AMD Instinct configurations, flexible networking options and high-speed NVMe matched to performance requirements.
What makes our service different
What makes HiTechCloud Bare Metal GPU different?
Dedicated GPU infrastructure, a high-speed network and deployment specialists keep AI workloads stable, secure and easy to scale.
Dedicated GPUs
Full use of the GPU, with no shared resources and no interference from other systems.
High-performance network architecture
Flexible infrastructure for AI training and inference with high-performance GPU clusters, high bandwidth and optimized node-to-node data transfer.
Easy workload migration
Optimized for NVIDIA and AMD GPU workloads, and supports migrating existing systems with minimal change.
AI expert support
Simplifies deployment with SLURM, containers and AI frameworks, backed by a specialist team for integration.
Flexible for inference
Elastic compute matched to actual demand, optimizing performance and cost for AI inference workloads.
Control over OS & software
Install the operating system, GPU drivers, CUDA, ROCm and frameworks your project requires.
Key benefits
Choose the right configuration for any AI workload
Supports both distributed training and AI inference on dedicated GPUs, with flexible networking options and storage configured for your performance and cost targets.
Cost optimization
Choose the right GPU, storage and billing cycle to balance budget against performance for large-scale AI.
Full control
Manage the OS, drivers, runtime, security policy, data and job scheduling to your own requirements.
Ready to scale
From GH200 inference to HGX H100, HGX B200, MI300X, MI325X and MI355X clusters for training.
High-speed networking
25 Gbps, 100 Gbps and 200 Gbps options, with 400 Gbps GPU interconnect on selected configurations.
Fast deployment
HiTechCloud advises on GPU, CPU, RAM, NVMe, frameworks and the operating approach.
Suits multiple workloads
Used for distributed training, model serving, HPC simulation, computer vision and GenAI in production.
Bare Metal GPU pricing
Choose a bare metal GPU for your AI workload
Prices exclude VAT. Selecting a billing cycle updates every price on the slider at once so configurations are easy to compare.
AI Workload Fit
Training cluster
Inference node
HPC simulation
GPU framework tuning
Configuration advice
Still unsure which configuration fits?
Choose the right GPU cluster
The HiTechCloud team helps you choose between training and inference clusters, size the cluster and advise on the right cost level for each use case.
Framework optimization
Support for choosing drivers, CUDA, ROCm, container runtime, SLURM, PyTorch, TensorFlow or a suitable MLOps stack.
Storage and network design
Advice on NVMe, networking from 25 Gbps to 200 Gbps and high-speed GPU interconnect to reduce bottlenecks on large datasets.
Southeast Asia
Scale with confidence across Southeast Asia
Deploy systems and applications closer to your users, reducing latency and meeting local regulatory requirements.
Bangkok
01- BKK-01
Ho Chi Minh
03- HCM-01
- HCM-02
- HCM-03
Ha Noi
02- HAN-01
- HAN-02
06Availability zones
20+CDN points of presence by region
1000+Customers
24/7Customer support
ISO/IEC 27017
ISO/IEC 27018
ISO/IEC 27001
SISA
SOC 2
Uptime Tier
TVRA
Suitable applications
Supporting 1,000+ businesses on their digital transformation journey
Fast-growing businesses and startups choose HiTechCloud for AI cloud solutions that are secure, high-performance, and easy to scale.
TrainingDistributed training & fine-tuning
LLM training, computer vision, multimodal AI, large checkpoints and complex data pipelines.
InferenceHigh-load AI inference
Serves chatbots, RAG, embeddings, recommendations and model serving at low latency.
HPCSimulation and research
Accelerate simulation, rendering, data science, computational workloads and large-scale data analysis.
MLOpsProduction AI platform
Build a job execution environment, manage models, store checkpoints and scale resources reliably.
FAQ
FAQ
Quick facts before choosing Bare Metal GPU at HiTechCloud.
Which workloads suit Bare Metal GPU?
Suited to AI training, fine-tuning, inference, HPC, simulation, computer vision, rendering and any workload needing dedicated GPUs.
How does it differ from a shared GPU?
Bare Metal GPU provides dedicated physical resources, giving you control over the OS, drivers, data and job scheduling, with more consistent performance.
Should you choose H100, B200, GH200 or AMD Instinct?
H100 and B200 suit training, fine-tuning and large-scale inference. GH200 suits cost-efficient inference. AMD Instinct suits training and workloads that need large VRAM.
Does HiTechCloud support framework deployment?
Yes. HiTechCloud advises on drivers, CUDA, ROCm, container runtimes, SLURM, PyTorch, TensorFlow, and MLOps as needed.
What billing cycles are available?
The service supports 1-, 3-, 6-, 12-, 24-, 36-, 48- and 60-month terms, depending on configuration.
Are prices inclusive of VAT?
Listed prices exclude VAT and may change with additional storage, network, operations, or custom deployment requirements.
HiTechCloud AI Infrastructure
Ready to deploy Bare Metal GPU for large-scale AI?
Contact HiTechCloud for advice on the GPU, CPU, RAM, NVMe, network, framework and billing cycle that fit best.
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