AI Inference Workstations
Run AI models locally with 96GB to 192GB of GPU memory. Deploy private AI on NVIDIA RTX PRO 6000 Blackwell hardware. No cloud dependency, no per-token costs, complete data privacy.
Choose Your Inference Tier
GPU VRAM determines which models you can run. Select the tier that matches your largest model requirement.
96 GB Tier
1x NVIDIA RTX PRO 6000 BlackwellRuns the vast majority of production AI models at full precision. Ideal for teams deploying a primary model for day-to-day use.
192 GB Tier
2x NVIDIA RTX PRO 6000 BlackwellFor the largest open-source models and multi-model serving. Run Llama 3 405B, serve multiple models concurrently, or handle heavy concurrent user loads.
AI Inference Workstation Lineup
Every system includes Twin NVMe storage, 32GB DDR5 system memory, and NVIDIA RTX PRO 6000 Blackwell GPUs with 5th-generation Tensor Cores.
Ryzen 9 AI Inference 96B Workstation
Best value single-GPU inference with outstanding single-thread performance
Core Ultra 9 AI Inference 96B Workstation
Intel platform with built-in AI acceleration and broad ISV support
Threadripper 9000 AI Inference 192B
Dual-GPU with high core count for large model serving
Threadripper Pro 9000 AI Inference 192B
Maximum PCIe bandwidth for optimal dual-GPU performance
Xeon 3500 AI Inference 192B
Intel enterprise platform with ECC system memory support
Model Compatibility Guide
See exactly which AI models run on each VRAM tier. All models listed run at full speed with no cloud dependency.
| VRAM Tier | Models You Can Run | Use Cases |
|---|---|---|
| 96 GB | Llama 3 70B (full precision FP16), Mixtral 8x22B, Llama 3 8B, Mistral 7B, CodeLlama, DeepSeek-V2 (quantized). Most open-source models fit in 96GB. | Chatbots, code generation, document analysis, RAG pipelines, content creation |
| 192 GB | Llama 3 405B (4-bit quantized), DeepSeek-V2 (full precision), multiple 70B models simultaneously, Llama 3 70B + Stable Diffusion XL (multi-model). Every open-source model available today. | Frontier model deployment, multi-model serving, high-concurrency APIs, enterprise AI platforms |
Why On-Premise AI?
Running AI models on your own hardware eliminates recurring cloud costs, keeps sensitive data in-house, and gives you complete control.
Data Privacy
Your data never leaves your facility. Critical for HIPAA, CMMC, legal, and financial AI workloads.
No Cloud Costs
Eliminate per-token and per-hour GPU rental fees. Pays for itself within 6-12 months vs. equivalent cloud compute.
Compliance Ready
On-premise AI is the preferred approach for HIPAA, CMMC 2.0, ITAR, and other regulatory frameworks.
Low Latency
Local inference eliminates network round-trips. Sub-100ms response times for chatbots, copilots, and automated workflows.
Frequently Asked Questions
Which inference tier is right for my AI workload?
Can I upgrade from 96GB to 192GB later?
How does on-premise AI compare to cloud AI in cost?
Is on-premise AI inference HIPAA and CMMC compliant?
What software comes pre-installed?
Can these workstations serve multiple users simultaneously?
What is the difference between Ryzen 9 and Threadripper for inference?
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Run AI On Your Terms
No recurring cloud fees. No data leaving your building. No vendor lock-in. Talk to our AI hardware team about the right inference workstation for your needs.