CortexGPU · Enterprise
B200 and RTX Pro 6000 capacity for serious AI workloads.
Enterprise GPU capacity for AI, health and life-science teams. Datacenter and workstation tiers, security controls and direct procurement for groups that need capacity planning and workload-specific compliance.
Infrastructure
Enterprise GPU capacity, not a marketplace.
Enterprise compute is for teams that need more than spot instances: direct procurement, capacity planning, encryption, audit logs and access controls for AI, health and science work. Requirements are agreed during onboarding.
- Datacenter B200 and workstation RTX Pro 6000 tiers
- Region planning with encryption by default
- Customer-managed keys and access controls
- Quote-based terms with capacity planning
- Procurement with or without $CORTEXDAO
Planned before provisioning
Every enterprise environment starts with a security review: data region, encryption, access roles and key ownership are agreed up front, so nothing sensitive runs on defaults.
Hardware
Datacenter tier and workstation tier.
Two GPU classes for two kinds of work. Both are quote-based and come with capacity planning.
NVIDIA B200
Blackwell architecture · 8× nodes
- Memory
- 192 GB HBM3e
- Bandwidth
- 8.0 TB/s
- Purpose
- Large training runs, fine-tuning, high-volume inference
- Workloads
- Foundation models, protein structure, genomics
When a job needs serious memory and throughput — foundation models, protein structure, genomics at scale — this is the tier.
NVIDIA RTX Pro 6000
Blackwell class · 8× nodes
- Memory
- 96 GB GDDR7
- Performance
- 125 TFLOPS SP
- Purpose
- Inference, rendering, mid-size training
- Workloads
- 3D, creative, model serving, research
Made for inference, rendering, mid-size training and 3D work: strong performance without a full datacenter footprint.
Use cases
Built for sensitive and research-grade workloads.
Enterprise compute suits teams that must settle procurement, capacity and security — encryption, access controls, data residency — before any GPU job runs.
Health AI
Training and inference for health models where access controls and regions are configured before deployment.
Life sciences
Reserved capacity for bioinformatics, drug discovery, genomics and scientific computing that needs predictable throughput.
Institutions
Universities and labs buying pooled compute for research groups, including grant-funded shared capacity.
Process
How enterprise procurement works.
Direct conversations. No marketplace queue.
- 01
Describe your workload
What you are building, expected runtime, preferred hardware, timeline, and any region or compliance limits.
- 02
Get a capacity plan and quote
We review the requirements and send back a quote with allocation, terms and procurement options.
- 03
Provision and onboard
Once terms are signed we provision the environment with encryption, access controls and monitoring switched on.
FAQ
Common questions.
Is there a minimum commitment?
Enterprise terms are shaped around your workload. We begin with your requirements and build a capacity plan. There is no fixed minimum, but this is not spot pricing.
Can I pay in crypto or $CORTEXDAO?
Enterprise deals are quote-based and can settle in crypto, fiat or $CORTEXDAO. The exact method is agreed on the first call.
Which compliance needs can you meet?
Compliance is scoped during onboarding. Environments can include chosen regions, encryption, access controls and customer-managed keys on request.
How quickly can I be provisioned?
It depends on available capacity and the workload. From first contact to a quote is usually a matter of days, not weeks.