AI Inference Rack – A40 Edition (70B Model Ready, Turnkey System)
Warranty: Lifetime
Deploy Private AI Infrastructure — Not Just a Server
Run 70B parameter language models locally with a fully integrated rack system built on enterprise hardware. No API costs. No data leaving your environment.
- Built on Dell PowerEdge R740xd platform
- Powered by NVIDIA A40 48GB
This is a complete AI infrastructure solution, delivered as a fully configured rack system:
- 2U GPU server (A40-powered)
- Enclosed rack cabinet (office or data center ready)
- Integrated networking
- Clean cable management
👉 Not a loose server. Not a DIY build.
👉 A deployable AI system.
SYSTEM ARCHITECTURE
Server Platform
- Model: Dell PowerEdge R740xd (2U rackmount)
- Enterprise-grade chassis designed for GPU workloads
- High static pressure airflow for passive GPUs
GPU
- 1× NVIDIA A40 (48GB VRAM)
- Supports:
- 70B LLMs (quantized)
- Multi-user inference workloads
CPU
- Dual Intel Xeon Scalable CPUs
- Example: 2× Xeon Silver 4210R (or equivalent)
Memory
- 128GB DDR4 ECC RDIMM (standard)
- Upgradeable to 256GB+
Storage
- 2TB NVMe SSD (enterprise-grade)
- Optional expansion for model libraries + datasets
Networking
- Dual 10GbE SFP+ (standard)
- Optional:
- 25GbE upgrade
- Fiber / DAC cabling packages
Power
- Redundant enterprise PSUs (1100W–1600W)
GPU Enablement (Pre-installed)
- Dell GPU enablement kit (risers, cables, airflow shroud)
- Fully configured for A40 compatibility
Included Rack Cabinet
- 18U enclosed rack cabinet
- Minimum 35” depth (server-compatible)
- Lockable front/rear doors
- Cable management rails
Why this matters:
Most AI systems ship as standalone servers.
This system is delivered as:
A complete, rack-mounted AI environment
WHAT YOU CAN RUN
Supported Workloads
- Llama 70B-class models (quantized)
- Internal AI assistants
- RAG (retrieval augmented generation)
- Document processing + search
- Secure enterprise AI workflows
Performance Expectations
- Sub-second response times (config dependent)
- Multi-user support
- Near-zero marginal cost per query
WHY THIS EXISTS
Cloud AI scales cost. This system does not.
- No per-token billing
- No external data exposure
- Predictable performance
- Ideal for organizations spending $1K–$10K/month on AI APIs
Deploy Private AI Infrastructure — Not Just a Server
Run 70B parameter language models locally with a fully integrated rack system built on enterprise hardware. No API costs. No data leaving your environment.
- Built on Dell PowerEdge R740xd platform
- Powered by NVIDIA A40 48GB
This is a complete AI infrastructure solution, delivered as a fully configured rack system:
- 2U GPU server (A40-powered)
- Enclosed rack cabinet (office or data center ready)
- Integrated networking
- Clean cable management
👉 Not a loose server. Not a DIY build.
👉 A deployable AI system.
SYSTEM ARCHITECTURE
Server Platform
- Model: Dell PowerEdge R740xd (2U rackmount)
- Enterprise-grade chassis designed for GPU workloads
- High static pressure airflow for passive GPUs
GPU
- 1× NVIDIA A40 (48GB VRAM)
- Supports:
- 70B LLMs (quantized)
- Multi-user inference workloads
CPU
- Dual Intel Xeon Scalable CPUs
- Example: 2× Xeon Silver 4210R (or equivalent)
Memory
- 128GB DDR4 ECC RDIMM (standard)
- Upgradeable to 256GB+
Storage
- 2TB NVMe SSD (enterprise-grade)
- Optional expansion for model libraries + datasets
Networking
- Dual 10GbE SFP+ (standard)
- Optional:
- 25GbE upgrade
- Fiber / DAC cabling packages
Power
- Redundant enterprise PSUs (1100W–1600W)
GPU Enablement (Pre-installed)
- Dell GPU enablement kit (risers, cables, airflow shroud)
- Fully configured for A40 compatibility
Included Rack Cabinet
- 18U enclosed rack cabinet
- Minimum 35” depth (server-compatible)
- Lockable front/rear doors
- Cable management rails
Why this matters:
Most AI systems ship as standalone servers.
This system is delivered as:
A complete, rack-mounted AI environment
WHAT YOU CAN RUN
Supported Workloads
- Llama 70B-class models (quantized)
- Internal AI assistants
- RAG (retrieval augmented generation)
- Document processing + search
- Secure enterprise AI workflows
Performance Expectations
- Sub-second response times (config dependent)
- Multi-user support
- Near-zero marginal cost per query
WHY THIS EXISTS
Cloud AI scales cost. This system does not.
- No per-token billing
- No external data exposure
- Predictable performance
- Ideal for organizations spending $1K–$10K/month on AI APIs