Private AI Infrastructure & Data-Center Infrastructure Consultant
We help founders, CTOs, and infrastructure leaders measure real workloads and deploy AI systems that run entirely inside their own network — from a DGX Spark on your desk to a private GPU cluster in a data center.
- Scope
- Local AI Workstations · Global GPU Broker
- Default Local Model
- Qwen3.8-27B NVFP4 W4A4 ≈86 tok/s aggregate
- Frontier Bench
- GLM-5.3-Flash · DeepSeek-V4-Flash
- Bulk Chip Sourcing
- H100 SXM5 · H200 · B200 · B300 · GB200 · GB300 · Vera Rubin (VR200)
- Data-Center Scope
- 1 MW to 50+ MW Liquid / Immersion
- Security Boundary
- Zero Cloud Egress for On-Prem Deployments
- Vendor Allegiance
- Independent / Buy-Side Sourcing
Measure the workload honestly. Buy only the hardware that fits.
Core Offerings
From a single desktop AI machine to full data-center deployments and independent GPU brokerage.
DGX Spark
Personal and desk. Frontier models at your desk, silent, standard 120V outlet.
Custom RTX PRO builds
Small and medium offices. Multi-GPU workstations built to the measured workload.
Custom deployments and private GPU clusters
Turnkey: hardware sourcing, data-center and colocation space, power, OEM sourcing, installation, load testing, and ongoing support. For teams that have outgrown a desk.
GPU brokerage and sourcing
Independent, buy-side procurement of GPUs, used servers, and data-center capacity. We source for you; we never resell capacity we operate ourselves.
When cloud rental falls short
Renting GPUs from cloud providers keeps getting harder — availability, allocation, rate limits, and bills that scale with usage. Owning the hardware flips that: fixed cost, no queue, no data egress. Whether it's one DGX Spark or a full cluster, we source, build, and support it — and we're independent, so the recommendation is driven by your workload, not our inventory.
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. Video and image input now ships in frontier open models (GLM-5.3-Flash, Qwen3.8-Flash-Next), so image and video pipelines can run on owned hardware with no cloud render or upload.
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.
Open-Source AI Model Sizing Matrix
Hardware requirements, quantization footprints, and generation speeds for running frontier models locally at home or in an office.
| Model & Architecture | Format | Memory Footprint | Speed | Recommended Hardware | Environment |
|---|---|---|---|---|---|
| Qwen3.8-27B Dense Reasoning (Default Trial) | NVFP4 | ~18 GB | ~86 tok/s | Single DGX Spark (128GB) | Home Office / Desk (Silent 32dB, 240W) |
| Qwen3.8-Flash-Next MoE ~180B / 6B active | 4-bit | ~93–111 GB | est. ~95 tok/s | Single DGX Spark (128GB) | Home Office / Desk (Silent 32dB) |
| DeepSeek-V4-Flash-0731 MoE 284B / 13B active | NVFP4 MoE | ~142 GB | est. ~115 tok/s | Dual Spark Link (256GB Unified) | Home Office / Workstation |
| GLM 5.2 Giant Multimodal MoE (Text/Image/Video) | NVFP4 MoE | ~148 GB | Measured on your trial (single-stream) | Dual Spark Link (256GB Unified) | Workstation / Small Office |
| GLM-5.3-Flash MoE 320B / 18B active (measured on our bench)* | EXL3 4-bit | ~164 GB | 78.8 tok/s 1-stream structured · 227.9 tok/s 4-stream aggregate (TensorFold) | Dual Spark Link (256GB Unified) | Workstation / Small Office |
| Llama-3.3-70B-Instruct Dense Standard | FP8 | ~74 GB | Measured on your trial (single-stream) | Single DGX Spark (128GB) | Home Office / Desk |
| Kimi-K1.5-LongContext 128K Ultra-long doc ingestion | NVFP4 | ~96 GB | ~38 tok/s | Single DGX Spark (128GB) | Home Office / Desk |
| DeepSeek-R1 (Full 671B)† Full frontier reasoning reference | FP8 / 4-bit | ~340–680 GB | ~28 tok/s | Quad Spark (512GB) / RTX PRO Cluster | Dedicated Rack / Private Data Center |
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
Frequently Asked Questions
Common technical questions on running open-source AI locally, hardware sizing for home and office, and on-premise infrastructure.
Ready to Measure Your Workload?
Schedule a 30-minute trial session or submit your workload details for a tailored assessment readout.