Train bigger.
Ship faster.
Pay less.
On-demand NVIDIA B200, H200, and H100 — from a single card to 8× NVLink nodes on 3.2 Tbps InfiniBand. Launch from the console, CLI, or Terraform and be training in under 90 seconds.
From $0.49/hr · Per-second billing · No egress fees
trainer-prod-01
8× H100 SXM · NVLink
finetune-llama
H100 SXM · 80 GB HBM3
sdxl-batch-eval
L40S · 48 GB GDDR6
Trusted by ML teams shipping in production
Fast models are built here
One platform for the whole lifecycle — burst training on NVLink nodes, inference that scales to zero, bare metal for steady state, and storage that keeps up with your dataloaders.
Take the tourGPU Cloud
On-demand B200, H200, and H100. Single GPUs to 8× NVLink nodes on a 3.2 Tbps InfiniBand fabric — launched in seconds, billed per second.
llama-70b-sft · 2× HGX H100
us-east-1 · reserved · NVLink + InfiniBand
16
GPUs
412k
tokens/s
96.4%
avg utilization
Serverless AI
Inference that scales to zero. Open-weight models behind autoscaling endpoints. Pay per token, not per idle GPU.
Bare Metal
Single-tenant EPYC and Xeon. Dedicated servers delivered in hours, with 20 TB of egress included.
Imaging RAID1 NVMe · ready in ~4 min
Storage
NVMe blocks, S3-compatible objects. Triple-replicated, attaches in seconds, free ingress always.
Networking
Private fabric, public numbers. VPC peering, 100 Gbps uplinks, and per-GPU metrics with zero agents.
0.9 ms
p50 intra-region
42 Gbps
egress right now
Pick your silicon, keep your setup
Same images, same fabric, same per-second meter across the fleet. Start on an A100, finish on a B200 — change one flag.
3.2 Tbps
InfiniBand connecting every node in a training cluster
99.9%
Uptime SLA in every region, credited automatically
<90s
Cold boot from create to CUDA-ready
1 second
Billing granularity — idle time costs you nothing
Trusted in production
From seed-stage labs to render farms, teams run their most important workloads on Reviosa — and keep their budgets intact.
All customer storiesYour terminal is the console
Everything the dashboard does, the CLI and API do faster. Script your whole fleet — create, snapshot, scale, destroy — and let per-second billing clean up after your experiments.
- One CLI for instances, volumes, snapshots, and SSH keys
- Terraform provider and REST API with full console parity
- Prebuilt images: PyTorch 2.7, CUDA 12.8, JAX, vLLM
- Per-second usage streamed straight to your billing dashboard
$ reviosa instances create --type h100-sxm --region us-east-1
✓ Reserved 1× NVIDIA H100 SXM · 80 GB HBM3 in US East (Ashburn)
✓ Image pytorch-2.7-cuda12.8 attached · 1.5 TB NVMe mounted
✓ finetune-llama running in 47s — $2.49/hr, metered per second
$ reviosa ssh finetune-llama
ubuntu@finetune-llama:~$ nvidia-smi --query-gpu=name --format=csv,noheader
NVIDIA H100 80GB HBM3
ubuntu@finetune-llama:~$ torchrun train.py --config sft.yaml
Epoch 1/3 ━━━━━━━━ loss 1.842 · 412 tok/s/gpu
Notes from the engine room
Introducing per-second billing for every instance type
Starting today, every Reviosa instance type bills by the second with a 60-second minimum. A nine-minute smoke test on an 8×H100 node now costs $2.75, not $18.32.
From notebook to production: vLLM endpoints on Reviosa
The distance between a working notebook and a production endpoint is smaller than it looks. Launch, serve, monitor, and load-test an OpenAI-compatible vLLM endpoint on Reviosa in an afternoon.
Why VRAM, not FLOPS, limits your batch size
Two H100 numbers matter more than TFLOPS ever will: 80 GB and 3.35 TB/s. A tour of where the bytes actually go in training and inference, and why memory hits the wall first.
Start training in minutes
Create an account, add a card, and launch your first GPU instance. Per-second billing means you only pay for what you use.
No minimum commitment · Cancel anytime · $10 free credit for new accounts