Now Available: NVIDIA B300 & B200

ELITE AI
COMPUTE.
INSTANT
ACCESS.

HyperVizeTM delivers frictionless access to the world's most powerful GPUs. From single instances for rapid prototyping to bare-metal HGX clusters for foundation training. Provisioned in under 60 seconds with pre-baked ML environments.

< 60s
Avg Provision Time
1 - 24x
GPU Scaling Range
50%
Spot Savings
user@hypervize: ~
$ hf-cli compute launch \
--type b200-1x \
--tier on-demand \
--env pytorch-jupyter \
--auto-deploy true
[==================================] 100%
[+] Allocating 1x NVIDIA B200 instance...
[+] Pulling PyTorch 2.3 environment...
[+] Injecting SSH keys and exposing ports...
Instance Online. Connect: ssh root@hf-node-492

COMPUTE TAILORED TO YOUR WORKLOAD

Whether you are iterating in a notebook or running a multi-node training job, HyperVizeTM abstracts the hardware complexity so you can focus on the code.

Agile & Spot Compute

Perfect for prototyping, fine-tuning, and burst workloads. Access fractional MIG slices or dedicated single GPUs. Cut costs by up to 50% using our interruptible spot pools.

  • 1/7th to 8x GPU Configs
  • Spot & On-Demand Pricing
  • Pre-installed ML Environments

Enterprise Bare Metal

Zero virtualization overhead. Gain root access to dedicated HGX clusters connected via non-blocking InfiniBand fabrics. Designed for foundation model training.

  • Uncontended HGX Clusters
  • 400Gbps+ InfiniBand
  • SLA Guarantees

Global Compute API

Never worry about availability zones. HyperVizeTM orchestrates a massive global pool of premium hardware, giving you a unified interface to provision compute instantly.

  • Hardware Liquidity
  • Unified Command Line
  • Fault Tolerance

LIVE HARDWARE INVENTORY

ALL INSTANCES INCLUDE BANDWIDTH & BASE OS, WITH CONFIGURABLE OPTIONS FOR ML FRAMEWORKS, STORAGE, AND MORE.

VIEW ENTERPRISE CONTRACTS →
Hardware Tier Specifications Network On-Demand Spot Price
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READY TO LAUNCH?

Create an account to access fractional spot compute instantly, or contact our engineering team to discuss dedicated cluster topology.