Blackwell Ultra · Server
NVIDIA HGX B300
8 GPUsper server
- Architecture
- Blackwell Ultra
- Form
- Server-scale, 8 GPUs
- Scale-up
- 5th-gen NVLink, 8-GPU domain
U.S. NeoCloud · Accelerated Research Computing
AI infrastructure, engineered for training and inference.
ARC Cloud provides GPU compute, dedicated clusters, managed operations, and model services for teams that train, fine-tune, and serve AI models. Our capabilities span infrastructure investment and development, systems engineering, and production operations.
- Training
- Pretraining, fine-tuning, and post-training on GPU Cloud or dedicated clusters
- Inference
- Dedicated inference capacity, managed model serving, and inference APIs
- AI Platform
- Resource allocation, scheduling, and visibility across teams
- NVIDIA systems
- HGX B300 and GB300 NVL72, with Vera Rubin planning
ARC stands for Accelerated Research Computing.
What customers run on ARC
Training and inference put different demands on the same infrastructure.
AI programs move from training to adaptation to production, and each stage stresses a different part of the system. We design the deployment around the stage you’re in.
Train
Pretraining and large-scale training
Long multi-node runs need fast collective communication, steady data throughput, and reliable checkpointing.
Often starts withDedicated AI Clusters
Adapt
Fine-tuning and post-training
Shorter, frequent runs adapt a base model to a domain or behavior, and evaluation decides what ships.
Often starts withGPU Cloud
Serve
Production inference
Live traffic, where latency, throughput, and concurrency determine the cost of every token.
Often starts withProduction Inference
Discover
AI for Science
Scientific models, simulation, and large research datasets, including cell and life-science research.
Often starts withGPU Cloud and research collaboration
Products
Services for every stage of an AI program.
Choose how you access compute, whether you need a private cluster, who operates it, and how your models reach production.
01
GPU Cloud
GPU compute without building the infrastructure.
Run training, fine-tuning, and inference on NVIDIA GPU instances or bare metal servers, on flexible terms or with reserved capacity.
Best forTeams that need GPUs soon and want to choose their level of host control.
02
Dedicated AI Clusters
A private cluster, designed around your models.
Multi-node clusters with compute, networking, storage, and scheduler engineered together and validated against your jobs.
Best forLarge training runs and organizations that need hardware isolation.
03
Managed AI Infrastructure
ARC operates the fleet. You run the models.
Day-to-day operation of your GPU environment, from monitoring and recovery to upgrades, expansion, and management across clusters.
Best forTeams that want production reliability without staffing a fleet operations group.
04
Production Inference
From trained model to production service.
Serving capacity, managed model runtimes, and application-facing APIs, tuned for latency, throughput, and cost per token.
Best forTeams putting models in front of users.
AI Platform
The layer that ties the services together.
The AI Platform decides which team gets which resources, when jobs run, and where they land, with the visibility to plan what comes next. It supports every ARC product, so moving from GPU Cloud to a dedicated cluster doesn’t mean relearning how your teams work.
MaaS
Model servicesProduction Inference, plus fine-tuning, post-training, and evaluation
PaaS
AI PlatformResource allocation, scheduling and job placement, task-level controls, resource visibility
IaaS
InfrastructureGPU Cloud and Dedicated AI Clusters: compute, networking, and storage
Operations
Managed AI InfrastructureARC can operate any of these layers, or your team can.NVIDIA accelerated computing
Choose the system form, then the generation.
An eight-GPU server scales out across a cluster network. A 72-GPU rack works as a single NVLink domain. Blackwell Ultra is NVIDIA’s current architecture, and Rubin is next.
Grace Blackwell Ultra · Rack
NVIDIA GB300 NVL72
72 GPUs36 Grace CPUs per rack
- Architecture
- Blackwell Ultra
- Form
- Rack-scale, liquid-cooled
- Scale-up
- 5th-gen NVLink, 72-GPU domain
Vera Rubin · Rack · Next generation
NVIDIA Vera Rubin NVL72
72 GPUs36 Vera CPUs per rack
- Architecture
- Rubin
- Form
- Rack-scale
- Scale-up
- 6th-gen NVLink, 72-GPU domain
GPUCPU
System names refer to NVIDIA platform families. Configuration, quantity, and delivery timing are confirmed for each engagement.
Running on Hopper today? We can plan H100 and H200 environments as part of a migration or expansion.
Compare GPU systemsWhy ARC can deliver
What stands behind each service.
Reliable AI capacity depends on decisions made long before the first job runs. ARC’s team covers each of them, from investment and sourcing to the runtime a model serves on.
01 · Capital
Invest
Infrastructure investment, asset strategy, and capacity planning.
02 · Supply chain
Source
Hardware sourcing, supplier management, and delivery coordination.
03 · Engineering
Build
Facility readiness, rack integration, networking, storage, commissioning, and validation.
04 · Operations
Operate
Fleet lifecycle, recovery, expansion, and management across clusters.
05 · Models
Optimize
Fine-tuning, evaluation, deployment, and inference runtime tuning.
Leadership
Founded by builders of AI systems and data center infrastructure.
ARC’s founders combine production machine learning with the development and financing of large-scale digital infrastructure.
Co-founder
Erran Li
AI Systems
Machine learning systems. IEEE Fellow and ACM Fellow; Adjunct Professor at Columbia University.
Co-founder
William Tiah
Infrastructure & Capital
Data centers and infrastructure finance. Nearly two decades across telecommunications and digital infrastructure.
What are you training or serving next?
Tell us about the model, the scale, and the timeline. Our infrastructure team will help you choose the service, the system, and the operating model.
Support: support@arccloud.com
For product issues, service disruptions, or technical assistance.
Security: security@arccloud.com
To report vulnerabilities, suspicious activity, or other security concerns.