Train, fine-tune, and serve AI models on the same GPU infrastructure. Start with one machine, keep control of the stack, and scale only when the workload asks for it.
No contracts · Hourly billing · Deploy in under 60 seconds
Accelerator
H100 ×1
80 GB
vRAM
Runtime
Ubuntu + CUDA
Network
High-speed fabric
Storage
Persistent NVMe
Billing
Pay as you go
● machine requested
│ drivers and runtime prepared
● ready for SSH 00:42
27+
GPU models
40+
data centers
$0.17
per hour from
<60s
to deploy
The same account, storage, API, and infrastructure from prototype to production.
Train
Move from a single experiment to distributed training on multi-GPU nodes with the same workflow. Keep checkpoints, datasets, and environments close to the compute.
Recommended GPUs
H100 · H200 · B200 · B300 · A100
Serve
Ship open-weight LLMs, vision models, and embeddings behind an OpenAI-compatible API. Start with a proven runtime, then bring a custom container when you need control.
Recommended GPUs
H100 · L40S · A100 · RTX 6000 Ada
Adapt
Run LoRA, QLoRA, or full-parameter tuning with persistent volumes for datasets and weights. Use familiar experiment tracking instead of rebuilding the environment.
Recommended GPUs
A100 · H100 · L40S · RTX 4090
No capacity planning required
Browse live inventory before creating an account. Choose the exact GPU, region, and configuration you need.
No contracts
Scale down or stop whenever you need.
Live inventory
See current GPUs before you commit.
API access
Automate launch and lifecycle actions.
Persistent data
Keep volumes beyond the machine.
Use the same infrastructure for interactive prototypes, scheduled jobs, and latency-sensitive production services.
Run LLaMA, Mistral, Qwen, and DeepSeek with continuous batching and PagedAttention.
ProductionDeploy detection, segmentation, OCR, and video pipelines close to your users.
Real-timeGenerate images and video with Flux, Stable Diffusion, and custom diffusion models.
High VRAMRun molecular dynamics, protein folding, climate simulation, and numerical workloads.
HPCGenerate embeddings and serve retrieval pipelines across millions of documents.
RetrievalAccelerate ETL, preprocessing, and feature engineering with RAPIDS and cuDF.
RAPIDSChoose the accelerator
Compare GPU memory, price, region, and deployment type.
Add the environment
Pick an OS, SSH key, persistent volume, or custom container.
Launch and connect
Create the machine and connect over SSH when it is ready.
Accelerator selected
H100 · 80 GB
Environment prepared
Ubuntu · CUDA · SSH
Machine ready
Connect and start work
Choose hardware and topology from technical requirements, while keeping procurement simple.
Drug discovery, genomics, medical imaging, and clinical NLP.
Risk modeling, fraud detection, forecasting, and document processing.
Generation, video processing, recommendations, and personalization.
Route optimization, demand forecasting, and warehouse vision.
Simulation, predictive maintenance, and network planning.
NLP, computer vision, and scientific computing without contracts.
Pick the GPU model, count, region, and deployment type you actually need.
Detach machine lifetime from the datasets, checkpoints, and model weights.
Launch, inspect, and terminate compute from scripts and CI workflows.
Hourly billing and no long contract when a workload changes direction.
Start without a sales call
Browse capacity, choose a machine, and connect. Scale later if the experiment becomes production.