Enterprise GPU Rack Server
A rackmount server with passive server GPUs for shared inference and selected fine-tuning, planned with your IT team before it is specified.
Status: Concept: specification subject to validation
Form factor: Rackmount, multi-GPU
Price: On request
Reviewed 27 Oct 2026
Who it is for
IT teams and enterprises deploying AI for many users.
- Private RAG
- Local LLM
- Fine-tuning
In the advisor, this build serves the Enterprise rackmount or discovery consultation category.
Configuration options
Ranges we choose from during validation. The final specification depends on your workload, software and environment.
| Part | Options |
|---|---|
| CPU | Dual-socket or high-core-count server processors, chosen for PCIe lanes and memory bandwidth |
| GPU | Two to eight passive server GPUs, in a chassis validated for them |
| Memory | 512 GB to several TB of registered ECC memory |
| Storage | NVMe arrays for models and vector stores; integration with existing storage |
Cooling, power and installation
Cooling
Passive server GPUs rely entirely on the chassis fans and airflow design. Only installed in a chassis validated for them.
Power
Rack power, redundant PSUs and circuit capacity are agreed with your facilities team before quoting.
Chassis
Server chassis with high-static-pressure fans and GPU airflow ducting; server-room acoustics.
Network
Data-centre networking; uplink speed and topology agreed with your network team.
Software examples
Examples we can install and configure. Compatibility is confirmed for your exact versions during validation, not assumed.
- vLLM or another serving stack
- Your orchestration (containers, Kubernetes) where it exists
- Monitoring integrated with your tools
Limits, assumptions and open questions
Limitations
- Loud and power-hungry: needs a server room or data centre, not an office.
- Lead times and configurations depend on component availability, confirmed at quotation.
Assumptions
- Server room or colocation available
- IT team involvement
- Shared, multi-user workloads
What we will ask you
- Rack space, power and cooling available?
- Expected users and models?
- Existing virtualisation or orchestration?
Start from the Enterprise GPU Rack Server
Tell us your workload and we will adapt this configuration, check compatibility, and quote it. No obligation.