Find dedicated GPU server and cluster rental options for AI training, inference, rendering, and other compute workloads. Compare NVIDIA A100, H100, H200, B200, and B300 requirements across providers.
Reference specifications checked October 9, 2026. Confirm the exact variant and application-usable memory in the provider proposal. Figures are not a statement of available inventory. Sources: NVIDIA GPU variants, H100 reference, HGX reference.
What are you building?
Inference
Share model size, precision, context length, concurrency, and response-time targets. Compare measured throughput and full deployment cost.
Training
Specify model scale, dataset size, GPU count, checkpoint storage, and communication needs across nodes.
Fine-tuning
Describe the base model, tuning approach, memory requirements, and job schedule before selecting a rental term.
GPU clusters
Review the node topology, private fabric, shared storage, software management, and responsibility for keeping the cluster healthy.
Compare the service around the GPU.
Evaluate dedicated access, CPU and RAM, local and shared storage, private networking, public bandwidth, software responsibilities, support, and contract terms. Hardware capabilities do not automatically establish which services a rental includes.
Over 25 years in the IaaS industry, with a heavy focus on compute. We help put the solution together, connecting server and GPU requirements with facility power, cooling, networking, and provider terms. Our colocation sourcing spans 1U fractional space to multi-megawatt deployments.
We help turn your workload requirements into a rental specification, then compare the complete provider offering. Review GPU configuration, included resources, networking, software responsibilities, and commercial terms together.
Single GPU systems, multi-GPU servers, and multi-node clusters
NVIDIA A100, H100, H200, B200, and B300 rental requests
CPU, RAM, storage, interconnect, and bandwidth requirements
Rental term, support scope, deployment timing, and scaling options