Trusted by ML research teams and developers worldwide
Platform Capabilities
NVIDIA Preferred Partner
Access to single and multi-GPU instances from 1 to 8 GPUs per node.
Engineer-Level Support
Support requests are handled directly by engineers familiar with AI training, cluster issues, and performance tuning.
High-Performance Infrastructure
H100, A100, A40, and Gaudi GPUs connected with fast networking and very fast network storage.
On-Demand or Reserved Nodes
Per-minute billing for on-demand use, with lower prices for dedicated machines.
No Egress Charges
Data can be moved out of the platform without additional transfer fees.
SOC 2 Compliant
Systems and processes follow SOC 2 controls.
Prices
Per-Minute Billing + Reserved Pricing. Scale up or down instantly with on-demand instances billed by the minute, or lock in lower rates with reserved pricing.
Type | vCPUs | Memory | Local Storage | GPU VRAM | Price | Interconnect |
|---|---|---|---|---|---|---|
NVIDIA H200 SXM | 208 | 2048 GB | 6x 3.8TB NVMe | 141 GB | Reserved only | RoCE 3200G |
NVIDIA H100 SXM | 208 | 1024 GB | 6x 3.8TB NVMe | 80 GB | $2.10 / GPU | IB 3200G |
NVIDIA A100 SXM | 208 | 1024 GB | 6x 3.8TB NVMe | 80 GB | $1.30 / GPU | IB 1600G |
NVIDIA A100 SXM | 128 | 1024 GB | 4x 3.8TB NVMe | 40 GB | $1.15 / GPU | IB 800G |
NVIDIA B200 SXM | 224 | 2048 GB | 6x 3.8TB NVMe | 180 GB | RoCE or IB 3200G |
NVIDIA H200 SXM
Reserved only
208
vCPUs
2048 GB
Memory
6x 3.8TB NVMe
Local Storage
141 GB
GPU VRAM
RoCE 3200G
Interconnect
NVIDIA H100 SXM
$2.10 / GPU
208
vCPUs
1024 GB
Memory
6x 3.8TB NVMe
Local Storage
80 GB
GPU VRAM
IB 3200G
Interconnect
NVIDIA A100 SXM
$1.30 / GPU
208
vCPUs
1024 GB
Memory
6x 3.8TB NVMe
Local Storage
80 GB
GPU VRAM
IB 1600G
Interconnect
NVIDIA A100 SXM
$1.15 / GPU
128
vCPUs
1024 GB
Memory
4x 3.8TB NVMe
Local Storage
40 GB
GPU VRAM
IB 800G
Interconnect
NVIDIA B200 SXM
224
vCPUs
2048 GB
Memory
6x 3.8TB NVMe
Local Storage
180 GB
GPU VRAM
RoCE or IB 3200G
Interconnect
Interested in deploying NVIDIA H100 GPUs for training, inference, or large-scale AI workloads?
Contact our team to discuss availability, configurations, pricing, and deployment options. We’ll help you determine the right solution to meet your performance and scalability needs.
Video Section Title
Video section description.
Meet Our Partner: Internal Technologies
Brief and catchy video description. Old content we can reuse: The GPU Cloud Marketplace multi−cloud management. Find the optimal GPU and cloud for your needs.
John Hanby IV | Founder and CEO
H100 Use Cases
Multi-GPU Training
H100 scales efficiently and reduces time to train, especially for large distributed runs with heavy communication and big batches.
LLM Inference at Scale
It delivers higher throughput and more stable latency under high concurrency, so you can serve more requests per GPU.
LLM Inference at Scale
It delivers higher throughput and more stable latency under high concurrency, so you can serve more requests per GPU.
RAG Pipelines
It helps keep end to end latency low, so embeddings, reranking, and generation stay responsive as your knowledge base and traffic expand.
Inference Comparison
Choose the most cost-effective enterprise GPUs.
Title | Llama 3 8B | Llama 3 70B | Qwen 2 72B | LLama 4 Maverick |
|---|---|---|---|---|
Nvidia A100 SMX 40G | Yes | No | Yes | FP16, 8 GPUs / 4 nodes |
Nvidia A100 SMX 80G | Yes | Yes | Yes | FP16, 8 GPUs / 2 nodes |
Nvidia H100 | Yes | Yes | Yes | FP8, 8 GPUs / 1 node |
