On demand GPU pricing

Model

VRAM (GB)

Max vCPUs per GPU

Max RAM (GB) per GPU

On-Demand Price (/hr)

1 Year price (/hr)

Nvidia H200

141

48

384

n/a

$2.45

Nvidia H100 PCIe

80

48

256

$2.89

$2.05

Nvidia A100 80GB PCIe

80

48

256

$1.80

$1.20

Nvidia A100 40GB PCIe

40

32

128

$1.65

$1.05

Nvidia L40

48

32

48

$1.25

$0.99

Volume discounts starting at 8+ GPUs.

Our reserved clusters are designed for large-scale training and inference, offering industry-leading turnaround times and unbeatable pricing.

24/7 MLOps support.

With a 15-minute response time and proactive debugging, all at no additional cost.

Fully managed K8s or Slurm.

So you don't have to worry about complex infrastructure and can focus on your models.

Starting at at $1.94/h.

Featuring fully interconnected Nvidia H100s with 3.2 Gbps non-blocking InfiniBand.

Large scale GPU clusters

Designed for large scale training and inference, deployed on our fully managed cloud infrastructure.

  • GPU Count

    8 – 10K+

  • Term

    30 days or longer

On-demand GPU instances

Launch GPU instances in under 5 minutes, and seamlessly scale to 100s of GPUs on-demand.

  • GPU Count

    1 - 100+

  • Term

    by the hour

Loved by the best AI Labs.

Poolside

Poolside

“One of the most important aspects of running an AI company is access to Compute. Fluidstack has been a phenomenal partner to Poolside. Large scale clusters are difficult to operate, but they’ve been exceptional. Their dedicated support is excellent, and they are able to provide a great service on top of the hardware.”

Jason Warner

CEO at Poolside

"Maximizing GPU power is essential for accelerating the time to market for advanced machine learning products like ours. However, managing GPU costs is equally crucial. At Fluidstack, we've discovered the perfect balance between performance and affordability."

Tigran Sargsyan

Director of Engineering at Krisp

"Fluidstack's support was excellent - which became especially important when deploying clusters at scale. Having a dedicated team to manage our cluster meant our engineers could focus on their workloads, and not have to worry about physical infrastructure."

Ugur Arpaci

DevOps Engineer at Codeway

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We can provision thousands of high-demand GPUs in record times, at the best prices. Skip the waitlist and start training now.