Vast.ai
GlobalGPU marketplace with flexible access to consumer and datacenter GPUs.
gpufleetContact →Find GPU capacity through trusted providers. We deploy and manage the Kubernetes GPU platform behind it, so your team can run production workloads without the operational complexity.
Compare 3 months, 6 months, 1 year, or all retained history using the median daily market low. Current data refreshes the latest point.
Prices are recorded daily. Each monthly point is the median of its daily market lows. Recorded history does not expire and is available under All. Current prices are indicative and are not a quote.
Compare hardware, pricing and availability across specialized GPU cloud providers.
GPU marketplace with flexible access to consumer and datacenter GPUs.
On-demand GPU cloud for AI, machine learning and container workloads.
GPU cloud infrastructure designed for AI development and training.
Specialized cloud infrastructure built for large-scale GPU workloads.
AI-focused cloud infrastructure with high-performance GPU compute.
GPU cloud infrastructure for AI training, inference and compute.
Distributed GPU cloud providing flexible and cost-efficient compute.
Cloud GPU infrastructure for AI training, inference and accelerated computing.
Hyperscale cloud GPU instances for AI training, inference and enterprise workloads.
Enterprise cloud GPU virtual machines for AI, HPC and accelerated computing.
Cloud GPU infrastructure for model development, training and scalable inference.
Developer-focused GPU Droplets for AI development, inference and training.
Some provider links may be referral links. gpufleet may earn a commission at no additional cost to you. GPU pricing and availability may change.
Estimate the cost of GPU capacity and the Kubernetes operations needed to run it, including partitioning, scheduling, and observability.
Estimates are based on configured GPU and gpufleet management options. Actual provider pricing may vary.
Get expert advice on GPU selection, cluster architecture, workload performance, and infrastructure costs.
Partition supported NVIDIA GPUs into isolated instances with dedicated compute and memory for Kubernetes workloads.
Share GPU access across development, testing, and intermittent workloads to make better use of available capacity.
Track GPU utilization, memory, and health with dashboards and alerts that help your team troubleshoot and plan capacity.
Planning a new cluster or improving the GPUs you already have? We help you assess your workloads, choose suitable infrastructure, and build a practical plan for performance, reliability, and cost.
Explore GPU consultancy →GPU compute costs depend on the provider and hardware you select. gpufleet focuses on helping you find, deploy and manage the right infrastructure.
Tell us what you are running and we can help you choose the right GPU infrastructure.
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