GPU Cloud · capacity available now

The newest GPUs.
The shortest commitments

Rent latest-gen GPU clusters by the week, not locked in for years. Orchestrated or bare metal, with a confirmed start date in 24 hours. Train and serve in one place.

No multi-year lock-in Start date in 24h Slurm, K8s or bare metal
baysn.ai · GPU fabric · live
ClustersNodesSlurm / K8s
Latest-gen
Newest GPUs, available now
0h
From request to a tailored proposal
Slurm · K8s
Orchestrated, or bare metal on request
Zero
Multi-year lock-in required

What's available

Newest GPUs, flexible terms

Orchestrated by default with Slurm or Kubernetes, bare metal on request. Short commitments on every configuration

Flagship · training

AI Labs

Frontier teams

Full training cluster, GPUs in tightly-coupled blocks with fast interconnect, high-capacity storage, and priority support. No multi-year lock-in required

Talk to us →
Startup · university

Startup & University

Fine-tuners · research

Latest-gen GPUs by the unit or the full node. Short-term, startup-friendly commitments on current hardware, on your timeline

Talk to us →
Dedicated

Dedicated Capacity

Steady production

Reserved GPUs for running your own models, isolated and yours alone. Burst onto larger clusters when you need headroom

Talk to us →
Prefer an API?

Baysn Inference

Ship in minutes

Don't want to manage the cluster? Call any open model through one OpenAI-compatible API, per-token or dedicated and private

Explore Inference →

The lineup

Pick the right silicon

Settled-price Hopper for fine-tuning, current-gen Blackwell for large runs, rack-scale for frontier pre-training. Every tier on short commitments, orchestrated or bare metal.

Value · Hopper

H100

80 GB HBM · available now

The settled-price workhorse. Fine-tuning, mid-scale training and inference where cost per GPU-hour matters most.

Reserve H100 →
Hopper

H200

141 GB HBM3e · available now

More memory per GPU for longer context and bigger checkpoints. Strong for fine-tuning and multi-node training today.

Reserve H200 →
Flagship · Blackwell Ultra

HGX B300

288 GB HBM3e · 8-GPU node · from late Aug

Current-gen training nodes, NVLink in-node and NDR InfiniBand across nodes. Built for large LLM and multimodal runs.

Reserve B300 →
Rack-scale

GB300 NVL72

72 GPUs · one NVLink domain · Q1 2027

72 Blackwell Ultra GPUs as a single coherent domain, liquid-cooled. Frontier pre-training at rack scale, reserve now.

Reserve NVL72 →

Memory and timing reflect current roadmap · interconnect and storage are tuned to your workload in the proposal

How it works

From conversation to compute in days

Tell us what you need, we put together a proposal, you deploy. No procurement gauntlet

1

Tell us what you need

Workload, GPU count, timeline. We come back with a tailored proposal within 24 hours

2

We allocate

Capacity is assigned in order. You get a confirmed start date, not a waitlist

3

You deploy

Spin up orchestrated Slurm or Kubernetes, or take bare metal. Train and run inference in the same place

Why Baysn

Newest hardware, shortest commitments

The latest GPUs without the multi-year contract. Orchestrated for you, or handed over bare metal. A start date, not a waitlist.

Latest-gen, available now

Current-generation clusters and nodes, ready to allocate. You get a confirmed start date, not a place in a queue.

Shortest commitments

The shortest terms on the newest hardware in the market. No multi-year lock-in. Rent by the week and structure it around your workload.

Orchestrated or bare metal

Slurm or Kubernetes managed by default, so your team just runs the work. Or take bare metal and own the whole stack. Your call.

The old way vs Baysn

Compute on your terms

How most GPU clouds make you buy, and how Baysn does it instead

The old way
  • Sign a one to three year contract
  • Wait months on a capacity queue
  • Get stuck paying for aging silicon
  • Stitch training and serving across providers
  • Grind through a procurement gauntlet
With Baysn
  • Shortest commitments, rent by the week
  • A confirmed start date, not a waitlist
  • Always on the newest GPUs
  • Train and serve in one place, no migration
  • A tailored proposal within 24 hours
The layer above · Inference

Just want to call a model?

If you don't need to manage a cluster, skip a layer up. Baysn Inference serves open models through one OpenAI-compatible API, per-token or dedicated and private, with a free API key in minutes

Explore Inference →

Get in touch

Tell us what you need

First allocations are being assigned now. We'll get back to you within 24 hours with a proposal tailored to your workload

No commitment required · we respond within 24 hours

GPU 101

New to GPU as a service?

Clear guides from our own team on what cloud GPUs are and how to rent the right amount

Read the full GPU 101 guide →

Questions

Common questions

What's the minimum commitment?

The shortest commitment terms on the latest GPU hardware in the market, no multi-year lock-in required. Talk to us about the right structure for your workload

When does capacity come online?

We're assigning the first allocation now. Reach out to get a confirmed start date for your workload

What's the difference between orchestrated and bare metal?

Orchestrated is our default managed product, Slurm or Kubernetes on dedicated resources, so your team runs training and inference without standing up the infrastructure. Bare metal is available on request. See GPU 101 for the full breakdown

Can I train and serve in the same place?

Yes. Run training on a cluster, then serve the model from the same facility, no moving data between providers. Many teams pair this with Baysn Inference for managed serving

I just want to call a model. Do I need a cluster?

No. Baysn Inference lets you call any open model through one OpenAI-compatible API, per-token or dedicated, without managing infrastructure. Same company, two ways to buy

We have the GPUs. You set the terms

Latest-gen capacity available now, shortest commitments in the market. Tell us what you need

Talk to us → Explore Inference