Published: July 3, 2026 | Category: Product Spotlight | QSCompute
Buying an RTX 6000 Ada is easy. Building a reliable workstation around it — with the right PCIe lanes, power delivery, cooling, and memory-to-GPU ratio — is where projects stall. We've done the integration work so you don't have to.
Below are three pre-configured RTX 6000 Ada systems, each purpose-built for a specific workload profile. Every system ships with a 48-hour burn-in test report, BIOS optimization guide, and pre-installed NVIDIA drivers + CUDA 12.6 toolkit. Plug in, power on, start inferring.
$12,800
| GPU | 1 × NVIDIA RTX 6000 Ada 48 GB GDDR6 ECC |
| CPU | Intel Xeon w7-2555X (14C/28T, 4.8 GHz boost) |
| Memory | 64 GB DDR5-5600 ECC (2 × 32 GB Samsung) |
| Storage | 2 TB Samsung 990 EVO Plus NVMe (7,250/6,300 MB/s R/W) |
| Chassis | Cincoze DX-1200 fanless, IP65, -25°C to 60°C |
| PSU | 850W industrial-grade, wide-input 19–36V DC |
| Networking | 2 × 10GbE SFP+, 2 × 2.5GbE RJ45, Wi-Fi 6E |
| OS | Ubuntu 24.04 LTS, CUDA 12.6, TensorRT-LLM, Docker |
Best for: Factory-floor vision inspection, on-premise LLM inference (7B–13B models at batch-8), AMR perception pipelines. Silent operation. Survives dust, vibration, and 50°C ambient.
$23,500
| GPU | 2 × NVIDIA RTX 6000 Ada 48 GB (96 GB total, no NVLink) |
| CPU | AMD Threadripper 7970X (32C/64T, 5.3 GHz boost) |
| Memory | 128 GB DDR5-5600 ECC (4 × 32 GB Samsung) |
| Storage | 2 TB Samsung 990 EVO Plus (OS) + 4 TB Samsung 870 EVO SATA (datasets) |
| Chassis | Fractal Design Define 7 XL, sound-dampened |
| Cooling | CPU: 360mm AIO; GPUs: stock axial — optimized airflow path |
| PSU | 1,600W 80+ Titanium (Seasonic Prime TX-1600) |
| Networking | 1 × 10GbE SFP+, 1 × 2.5GbE RJ45 |
| OS | Ubuntu 24.04 LTS, CUDA 12.6, PyTorch 2.5, Jupyter, vLLM |
Best for: LoRA/QLoRA fine-tuning of 7B–70B parameter models, multi-model inference serving (vLLM with tensor parallelism across 2 GPUs), dataset preprocessing at scale. 32 cores for ETL pipelines that feed the GPUs. Quiet enough for an office — 38 dBA under full load.
$44,800
| GPU | 4 × NVIDIA RTX 6000 Ada 48 GB (192 GB total) |
| CPU | Dual Intel Xeon 6530 (32C/64T each, 64C/128T total) |
| Memory | 256 GB DDR5-5600 ECC (8 × 32 GB Samsung) |
| Storage | 2 × 2 TB Samsung 990 EVO Plus NVMe (RAID 1 OS) + 8 TB U.2 NVMe (model cache) |
| Chassis | Supermicro SYS-421GU-TNXR, 4U short-depth (550mm) |
| Cooling | 8 × 92mm hot-swap fans, GPU-optimized shroud. Optional liquid cooling add-on. |
| PSU | 2 × 2,600W redundant 80+ Titanium |
| Networking | 2 × 25GbE SFP28, 4 × 10GbE SFP+, BMC/IPMI |
| OS | Ubuntu 24.04 LTS, CUDA 12.6, vLLM, Slurm, Prometheus + Grafana |
Best for: High-throughput LLM serving (Llama-3-70B INT4 across 4 GPUs with tensor parallelism), on-prem RAG pipelines with concurrent users, production inference with 24/7 uptime SLAs. Redundant PSUs, hot-swap everything, IPMI remote management. Short-depth chassis fits standard 800mm racks.
| Factor | Self-Build | QSCompute Pre-Configured |
|---|---|---|
| Component compatibility risk | High — GPU clearance, PCIe bifurcation, PSU rail sizing | Zero — every config is validated and benchmarked |
| Burn-in testing | Your problem | 48-hour GPU + memory stress test with report |
| BIOS optimization | Trial and error — Resizable BAR, Above 4G Decoding, PCIe Gen speeds | Pre-configured, documented settings sheet included |
| Driver/CUDA compatibility | Version hell — CUDA 12.4 vs 12.6, driver 550 vs 560 | Validated software stack, one apt update away |
| Warranty | Per-component, multiple vendors | Single point of contact, 3-year on-site, cross-ship RMA |
| Time to first inference | 2–4 weeks (sourcing, assembly, debugging) | 48 hours from order to burn-in complete |
Need something different? We build to your spec:
RTX 6000 Ada workstations in stock — pre-configured, burn-in tested, ready to ship.
Tell us your workload and we'll spec the right configuration. Single node evaluation to production fleet.
Contact: +86 189-9192-7716 | info@qscompute.com