Run Large Language Models Locally
Three AMD Radeon™ AI Pro R9700 GPUs with 96 GB total VRAM deliver high-performance local AI inference, RAG, coding assistants, and enterprise AI workloads on an open Ubuntu + ROCm™ stack.
Run LLMs Locally
Deploy 70B-class language models without the cloud. Large combined GPU memory enables longer context windows, faster inference, and secure on-prem deployment.
Open Software Stack
Ubuntu + AMD ROCm™ give you an open, standards-based platform for PyTorch, vLLM, and the broader open-source AI ecosystem — no vendor lock-in.
Private AI Infrastructure
Keep sensitive business data on-premises while cutting recurring cloud costs — purpose-built for organizations that require secure, offline AI computing.
Powered By an All-AMD Platform
Designed for Modern AI Workloads
Local LLM Inference
- ›70B-class language models
- ›AI chatbots
- ›Long-context inference
- ›Multi-user AI
AI Agents & RAG
- ›Enterprise knowledge base
- ›Document search
- ›AI Agents
- ›RAG pipelines
Private AI Platforms
- ›Open WebUI
- ›Ollama
- ›Onyx
- ›Private GPT
AI Inference Deployment
- ›OpenAI-compatible APIs
- ›Multi-model serving
- ›Production inference
- ›AI services
96 GB of combined GPU memory
Three AMD Radeon™ AI Pro R9700 GPUs pool into a single large memory footprint — handling larger models and longer context windows than a typical single-GPU workstation.
High-Performance Hardware
Why Choose This AI Workstation?
GPU Memory
Handle larger AI models and longer context windows than traditional single-GPU systems.
Open AI Stack
Ubuntu + AMD ROCm™ run PyTorch, vLLM, and open-source models with no vendor lock-in.
Enterprise Reliability
Server-grade memory, a workstation-class platform, and high-speed networking for continuous operation.
