Private Local AI Infrastructure
From a single DGX Spark on a desk to a private multi-node cluster, your documents never leave the building.
- Default Trial Model
- Qwen3.8-27B BF16 / FP8 / NVFP4 W4A4
- Frontier Bench
- GLM 5.2 · DeepSeek-V4-Flash-0731
- Available Models
- 9 Models pre-configured
- Serving Stack
- vLLM · SGLang · Open WebUI
- Precision Paths
- NVFP4 / FP8 / MXFP4 / Q8 / BF16
- Fine-Tuning
- Private On-Prem Training
- Security Boundary
- Zero External API Calls
Measure the workload honestly. Buy only the hardware that fits.
Choose Your Path to Private AI
Select an offering below to explore specs, benchmarks, and deployment options.
Test a Model
Get 30 minutes of direct access via Open WebUI or an OpenAI-compatible API endpoint. Test 9 models on local hardware with zero cloud API dependencies.
• NVFP4, FP8, BF16 Paths
• Zero External API Logs
Private AI Assessment
Measure your actual document prompts, traffic pattern, and user concurrency. We calculate tokens/sec, latency, memory footprints, and cloud cost crossover.
• Concurrency Limits
• Cost Crossover Analysis
Hardware Deployment
Dedicated desktop boxes, multi-system Spark links, custom RTX PRO 6000 workstations, or private multi-node clusters. Fully pre-loaded and load-tested.
• Dual/Quad Spark Links
• RTX PRO & Private Clusters
Agents & Fine-Tuning
We build custom AI agents and fine-tune model weights directly on your hardware. Tailored to your internal operations, customer support, and domain workflows.
• Private On-Prem Training
• You Own 100% of Weights
Measure First. Buy Second.
Most teams buy hardware first and hope for the best. We reverse that process: prove the workload runs locally, capture performance metrics, then select hardware that fits.
30 minutes on a private model
Connect via Open WebUI in your browser or point your tooling at an OpenAI-compatible endpoint on the same machine. Judge quality and integration yourself.
Explore Models →Your workload, measured
Your documents, your traffic pattern, your user count. We measure tokens per second, first-token latency, p95, concurrency, and cost crossover.
See Assessment Details →The readout picks the box
Deploy a DGX Spark, a dual/quad Spark link, a custom RTX PRO 6000 workstation, or a private cluster. Every recommendation is driven by data.
View Hardware Specs →Your Data Stays in the Building
Data Control
Run AI over privileged, regulated, or proprietary material without turning every prompt into an external API call. What gets indexed stays on your hardware.
Usage Control
When the hardware is yours, nobody hits a usage cap, rate limit, or subscription tier mid-task. Capacity is a machine you own, not a meter.
Cost Control
For steady workloads, local inference turns a variable token bill into a fixed infrastructure decision. The assessment shows where the crossover sits.
Tailored for Regulated Workloads
Local AI excels in document-heavy, data-sensitive operations where retrieval over private files serves as the primary workflow.
Legal
Matter-file Q&A and contract clause comparison without opening privileged documents to a cloud log.
Healthcare
Chart abstraction and clinical Q&A on PHI that never leaves the building.
Finance
Deal-room and trading-desk document search with no third-party vendor exposure.
Research
Air-gapped literature synthesis and code analysis for ITAR/CMMC environments.
Creative
Unreleased-asset image and video pipelines with no cloud render bills or embargo leaks.
Who's Behind It
GPUNexus is led by an infrastructure specialist who works directly with AI teams evaluating GPU compute for training, post-training, and inference.
We operate vendor-neutrally: measure the workload honestly, and buy only the hardware that fits.
Read Full Founder Story & Principles →- Recommendation Source
- The Workload
- If One Box Works
- Use One Box
- If It Doesn't
- Scale with Measured Data
- Vendor Allegiance
- None
Ready to Measure Your Workload?
Schedule a 30-minute trial session or submit your workload details for a tailored assessment readout.