AxonGPU · Enterprise

B200 and RTX Pro 6000 capacity for serious AI workloads.

Enterprise GPU infrastructure for AI, healthcare, and life sciences. B200 datacenter GPUs and RTX Pro 6000 workstation GPUs. Oracle Cloud Infrastructure partnership, security controls, and direct procurement for teams that need capacity planning and workload-specific compliance requirements.

Infrastructure

Enterprise GPU infrastructure, not a marketplace.

Enterprise compute is built for teams that need more than spot instances. Direct procurement, capacity planning, and encrypted infrastructure with audit logs and access controls for AI, healthcare, and scientific workloads. Requirements are discussed during onboarding.

  • B200 and RTX Pro 6000 GPUs through Oracle Cloud Infrastructure
  • US-based regions with encryption-by-default
  • Customer-managed keys and access controls
  • Quote-based terms with capacity planning
  • Token-optional procurement paths available
Request enterprise quote
Partnership

Oracle Cloud Infrastructure

Announced February 2026. Enterprise GPU infrastructure is built on OCI with security controls, access controls, region planning, and customer-managed key options available on request.

Hardware

Datacenter-class and workstation-class.

Two GPU tiers for different workload profiles. Both quote-based with capacity planning.

Datacenter

NVIDIA B200

Blackwell architecture · 8× configuration

Memory192 GB HBM3e
Bandwidth8.0 TB/s
PurposeLarge-scale training, fine-tuning, high-throughput inference
WorkloadsFoundation models, protein folding, genomics

If the workload demands serious memory and compute — foundation model training, protein folding, genomics at scale — this is the GPU.

Workstation

NVIDIA RTX Pro 6000

Blackwell-class · 8× configuration

Memory96 GB GDDR7
Performance125 TFLOPS SP
PurposeInference, rendering, mid-scale training
Workloads3D, creative, inference serving, research

Built for inference, rendering, mid-scale training, and 3D/creative workloads: power without the full datacenter footprint.

Use cases

Built for sensitive and research-grade workloads.

Enterprise compute is designed for teams that need procurement, capacity planning, and security requirements like encryption, access controls, and region-specific data residency before using GPU infrastructure.

Healthcare AI

Training and inference for healthcare AI models where security controls, access controls, and region planning are configured before deployment.

Life sciences

GPU capacity for bioinformatics, drug discovery, genomics, and scientific computing workloads that need predictable, reserved compute.

Institutional

Universities and institutions buying compute access for their research teams, including shared compute pools for research groups and grant-backed infrastructure.

Process

How enterprise procurement works.

Direct conversations. No marketplace queues.

01

Tell us about your workload

What you are building, expected runtime, hardware preference, timeline, region or compliance constraints.

02

Receive a capacity plan and quote

We review your requirements and return a quote with capacity allocation, terms, and procurement options.

03

Provision and onboard

Once terms are agreed, we provision your environment with encryption, access controls, and monitoring in place.

FAQ

Common questions.

What is the minimum commitment?

Enterprise procurement is tailored to your workload. We start with your requirements and build a capacity plan — there is no fixed minimum, but this is not spot-market pricing.

Can I pay with crypto or AXGT?

Enterprise procurement is quote-based and supports flexible payment options including crypto, fiat, and AXGT tokens. Specific payment methods are discussed during your first call.

What compliance requirements can you support?

Compliance requirements are discussed during onboarding. Infrastructure may include OCI regions, encryption, access controls, and customer-managed key options available on request.

How fast can I get provisioned?

Provisioning timeline depends on capacity availability and workload requirements. From first contact to quote is typically days, not weeks.