Office or studio · 4 systems
SME workstations
Direct, user-adjacent systems for one or two GPUs where a rack is unnecessary.
- GPU span
- 1–2 GPUs
- Installed GPU memory
- 32GB–192GB
11 systems / 3 deployment classes
Compare GPU Server Prices Before You Buy AI & LLM Workstations
Filter by system class, GPU count, VRAM, workload and facility. Every result shows its price, key limitations and model compatibility.
All 11 systems before filtering
See the complete 4 / 5 / 2 range before narrowing it.
Every controlled product is visible here: four SME workstations, five enterprise PCIe racks and two frontier systems. Open a system directly or send a whole class into the catalogue filters.
Server room or colocation · 5 systems
Enterprise PCIe racks
Serviceable rack systems for shared workers, higher density and remote operation.
- GPU span
- 4–8 GPUs
- Installed GPU memory
- 128GB–1,128GB
- Value Rack 128 4 × 32GB ↗
- Value Rack 256 8 × 32GB ↗
- Enterprise 384 4 × 96GB ↗
- Enterprise 768 8 × 96GB ↗
- H200 1.1TB 8 × 141GB ↗
Specialist data centre · 2 systems
Frontier systems
Tightly coupled HGX and full-rack infrastructure for demanding programmes.
- GPU span
- 8–72 GPUs
- Installed GPU memory
- 2,304GB–20,736GB
Matching systems
Matching systems stay visible while filters change.
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No system satisfies every selected control.
Remove one constraint or tell us what you need. An empty result is preferable to suggesting an unsuitable system.
SME workstation range
Four tower systems, from one 32GB GPU to two 96GB GPUs.
Compare form, GPU configuration, per-GPU and aggregate memory, system resources, power planning, representative fit and the first limitation before price becomes the deciding factor.
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Reference system 01
Team 32
Workstation-family reference image · appearance varies by configuration WorkstationA selected-supplier RTX 5090 tower for controlled local chat, RAG, coding, speech, image and batch evaluation when the accepted workload fits one 32GB GPU.
- GPU configuration
- 1 × NVIDIA GeForce RTX 5090 32GB
- GPU count
- 1
- Per GPU
- 32GB VRAM
- GPU memory
- 32GB one GPU
- System memory
- 64GB
- Primary storage
- 2TB NVMe
32GB is available on one GPU as one physical memory space.
Power planning
Specified for the ordered configuration and intended facility.
Representative fit
One team beginning a controlled local-AI deployment
Check before selection
32GB is one GPU's physical memory; context, cache, batching and concurrency reduce the usable model envelope.
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Reference system 02
Company 64
Workstation-family reference image · appearance varies by configuration WorkstationA supplier-validated dual-GPU workstation for teams needing two local workers or qualified PCIe sharding, with no NVLink or pooled-memory claim.
- GPU configuration
- 2 × NVIDIA GeForce RTX 5090 32GB
- GPU count
- 2
- Per GPU
- 32GB VRAM
- Physical total
- 64GB not automatically pooled
- System memory
- 128GB
- Primary storage
- 2TB NVMe
64GB is the physical total across 2 separate 32GB GPUs. It is not automatically pooled; supported software may divide a model or workload across them, subject to topology and testing.
Power planning
Specified for the ordered configuration and intended facility.
Representative fit
Two independent private AI or creative queues
Check before selection
64GB is aggregate capacity across two 32GB GPUs, not one universal memory pool.
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Reference system 03
Studio 96
Workstation-family reference image · appearance varies by configuration WorkstationA selected-supplier RTX PRO 6000 Blackwell workstation for named models and professional workloads that need substantially more than 32GB on one GPU.
- GPU configuration
- 1 × NVIDIA RTX PRO 6000 Blackwell 96GB
- GPU count
- 1
- Per GPU
- 96GB VRAM
- GPU memory
- 96GB one GPU
- System memory
- 128GB
- Primary storage
- 2TB NVMe
96GB is available on one GPU as one physical memory space.
Power planning
Specified for the ordered configuration and intended facility.
Representative fit
A named model or creative workload that benefits from 96GB on one GPU
Check before selection
The exact RTX PRO 6000 Workstation or Max-Q selection remains a pre-quote decision.
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Reference system 04
Studio 192
Workstation-family reference image · appearance varies by configuration WorkstationA supplier-validated dual RTX PRO tower for studios and technical teams, explicitly treated as 192GB aggregate capacity rather than one pooled memory space.
- GPU configuration
- 2 × NVIDIA RTX PRO 6000 Blackwell 96GB
- GPU count
- 2
- Per GPU
- 96GB VRAM
- Physical total
- 192GB not automatically pooled
- System memory
- 128GB
- Primary storage
- 2TB NVMe
192GB is the physical total across 2 separate 96GB GPUs. It is not automatically pooled; supported software may divide a model or workload across them, subject to topology and testing.
Power planning
Specified for the ordered configuration and intended facility.
Representative fit
Two independent high-memory professional GPU services
Check before selection
192GB is aggregate capacity across two 96GB GPUs, not one universal memory pool.
Model compatibility
25 models fit without splitting the model across GPUs ; 2 more need multi-GPU validation.
See compatible models
* Aggregate VRAM is a hardware total, not a promise that every workload can use it as one memory pool. Confirm the exact model, runtime and parallelisation route.
PCIe rack range · high-memory H200 option
Five rack systems for shared workers and enterprise operation.
Choose by GPU layout, per-GPU memory, workload and facility needs. H200 adds a high-memory eight-GPU option.
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Reference system 01
Value Rack 128
GENOAX2 platform-family image showing a representative internal layout Rack serverFour PCIe Gen5 GPU workers for batch, private inference and service queues, supplied as one configured enterprise system.
- GPU configuration
- 4 × NVIDIA RTX 5090 AI 32GB
- GPU count
- 4
- Per GPU
- 32GB VRAM
- Physical total
- 128GB not automatically pooled
- System memory
- Specified to order
- Primary storage
- Specified to order
128GB is the physical total across 4 separate 32GB GPUs. It is not automatically pooled; supported software may divide a model or workload across them, subject to topology and testing.
Power planning
Specified for the ordered configuration and intended facility.
Representative fit
Four independent GPU services or queues
Check before selection
128GB is aggregate capacity across four 32GB GPUs.
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Reference system 02
Value Rack 256
GENOAX2 platform-family image showing a representative internal layout Rack serverEight PCIe Gen5 GPU workers for dense batch and service throughput. Selection depends on sustained utilisation, final topology, GPU warranty and facility acceptance.
- GPU configuration
- 8 × NVIDIA RTX 5090 AI 32GB
- GPU count
- 8
- Per GPU
- 32GB VRAM
- Physical total
- 256GB not automatically pooled
- System memory
- Specified to order
- Primary storage
- Specified to order
256GB is the physical total across 8 separate 32GB GPUs. It is not automatically pooled; supported software may divide a model or workload across them, subject to topology and testing.
Power planning
Specified for the ordered configuration and intended facility.
Representative fit
Eight independent services or parallel batch queues
Check before selection
256GB is aggregate capacity across eight 32GB GPUs.
Model compatibility
18 models fit without splitting the model across GPUs ; 5 more need multi-GPU validation.
See compatible models -
Reference system 03
Enterprise 384
GENOAX2 platform-family image showing a representative internal layout Rack serverFour RTX PRO 6000 Blackwell Server Edition GPU workers for controlled enterprise services, with platform, cooling and support brought together.
- GPU configuration
- 4 × NVIDIA RTX PRO 6000 Blackwell 96GB
- GPU count
- 4
- Per GPU
- 96GB VRAM
- Physical total
- 384GB not automatically pooled
- System memory
- Specified to order
- Primary storage
- Specified to order
384GB is the physical total across 4 separate 96GB GPUs. It is not automatically pooled; supported software may divide a model or workload across them, subject to topology and testing.
Power planning
Specified for the ordered configuration and intended facility.
Representative fit
Several 96GB private inference endpoints
Check before selection
384GB is aggregate capacity across four 96GB GPUs.
Model compatibility
25 models fit without splitting the model across GPUs ; 5 more need multi-GPU validation.
See compatible models -
Reference system 04
Enterprise 768
GENOAX2 platform-family image showing a representative internal layout Rack serverEight RTX PRO 6000 Blackwell Server Edition GPU workers for large private platforms where independent services or tested sharding justify the facility requirements.
- GPU configuration
- 8 × NVIDIA RTX PRO 6000 Blackwell 96GB
- GPU count
- 8
- Per GPU
- 96GB VRAM
- Physical total
- 768GB not automatically pooled
- System memory
- Specified to order
- Primary storage
- Specified to order
768GB is the physical total across 8 separate 96GB GPUs. It is not automatically pooled; supported software may divide a model or workload across them, subject to topology and testing.
Power planning
Specified for the ordered configuration and intended facility.
Representative fit
Eight high-memory endpoints or batch workers
Check before selection
768GB is aggregate capacity across eight 96GB GPUs.
Model compatibility
25 models fit without splitting the model across GPUs ; 6 more need multi-GPU validation.
See compatible models -
Reference system 05
H200 1.1TB
H200-capable GENOAX2 platform-family image showing a representative eight-GPU topology and internal layout Rack serverA quote-only eight-GPU PCIe H200 NVL system for qualified large-model work. Kimi K3 and other large models require an exact runtime profile and acceptance test.
- GPU configuration
- 8 × NVIDIA H200 NVL 141GB
- GPU count
- 8
- Per GPU
- 141GB VRAM
- Physical total
- 1128GB not automatically pooled
- System memory
- 1024GB
- Primary storage
- 11.68TB NVMe
1,128GB is the physical total across eight H200 GPUs. It is not automatically one pooled memory space; supported parallel operation depends on the selected topology and runtime.
Power planning
Specified for the ordered configuration and intended facility.
Representative fit
A named large model with a reproduced eight-GPU profile
Check before selection
1,128GB aggregate HBM is below the current 1.5609TB official Kimi K3 weight-file total.
Model compatibility
25 models fit without splitting the model across GPUs ; 6 more need multi-GPU validation.
See compatible models
* Aggregate VRAM is a hardware total, not a promise that every workload can use it as one memory pool. Confirm the exact model, runtime and parallelisation route.
Frontier data-centre systems
Native HGX B300 and full-rack GB300 NVL72.
Both are configured to order for specialist data-centre projects. Compare GPU memory with the intended models, software, workload and performance requirement.
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Reference system 01
Frontier Native 2.3TB
SYS-822GS-NB3RT B300 platform reference image Rack serverA quote-only HGX B300 route using eight 288GB SXM GPUs and NVLink/NVSwitch architecture, subject to exact OEM configuration, software support and facility design.
- GPU configuration
- 8 × NVIDIA B300 288GB
- GPU count
- 8
- Per GPU
- 288GB VRAM
- Physical total
- 2304GB not automatically pooled
- System memory
- Specified to order
- Primary storage
- Specified to order
2,304GB is distributed across eight B300 GPUs connected by HGX NVLink and NVSwitch. The fabric enables high-bandwidth multi-GPU work, but software support and the exact workload still determine usable capacity.
Power planning
Specified for the ordered configuration and intended facility.
Representative fit
A named model with a validated HGX B300 runtime
Check before selection
2.304TB HBM is a calculated capacity envelope, not proof that the official Kimi K3 checkpoint loads or serves one-million-token context.
Model compatibility
30 models fit without splitting the model across GPUs ; 3 more need multi-GPU validation.
See compatible models -
Reference system 02
Frontier Rack 20TB
GB300 NVL72 rack architecture reference image Rack serverA quote-only GB300 NVL72 route with 72 Blackwell GPUs and 36 Grace CPUs. It is a complete rack-scale platform, not an ordinary GPU server.
- GPU configuration
- 72 × NVIDIA GB300 288GB
- GPU count
- 72
- Per GPU
- 288GB VRAM
- Physical total
- 20736GB not automatically pooled
- System memory
- Specified to order
- Primary storage
- Specified to order
20,736GB is distributed across a rack-scale NVLink and NVSwitch fabric. It is specialist shared infrastructure, not one ordinary GPU memory space.
Power planning
Up to 142kW full-rack power
Representative fit
A validated rack-scale model or training architecture
Check before selection
This is a complete 72-GPU liquid-cooled rack, not an the selected OEM 4U product or ordinary office delivery.
Model compatibility
30 models fit without splitting the model across GPUs ; 3 more need multi-GPU validation.
See compatible models
* Aggregate VRAM is a hardware total, not a promise that every workload can use it as one memory pool. Confirm the exact model, runtime and parallelisation route.
Included baseline
Specified, configured, tested and handed over.
The listed price covers the physical build, initial software configuration and documented remote onboarding. It is not a promise of open-ended implementation or a managed service.
- Itemised hardware specification
- Ubuntu and validated NVIDIA software pairing
- One agreed inference runtime and browser interface
- Model source and licence record
- 24-hour minimum burn-in and test evidence
- Credential and security-baseline handover
- Remote onboarding
- 30-day configuration-defect support
Do not choose from a card
Give the workload a chance to reject the hardware.
The right outcome may be a smaller machine, cloud service, colocation, hybrid service - or no purchase.
Decision check
GPU Server Price: Compare Like-for-Like Prices
For GPU server price, compare the complete configured system rather than the accelerator headline alone.
A useful GPU server price comparison should show the specification, evidence status, facility needs and quotation boundary. Include AI requirements, workstation form and LLM requirements where those factors change the decision.