REFERENCE DESIGNPALLADIUM-16
PALLADIUM-16 — entry fine-tuning node.
An entry fine-tuning node: one RTX 5080 with 16 GB, quiet enough to sit under a desk, sized for the models a first private deployment actually runs.
NVIDIA RTX 5080
16 GB
PALLADIUM-16
Entry fine-tuning node
Best for QLoRA fine-tuning of 7B–14B models and bf16 LoRA up to about 8B, small-batch inference, RAG indexing, and Jupyter-based research. Fits under a desk in a mid-tower, idles around 85 W, and takes about three hours from boxes to first boot.
Bill of materials
| GPU | 1× RTX 5080 — 16 GB GDDR7, Blackwell SM, PCIe 5.0 ×16, 256-bit, 960 GB/s, 360 W TDP |
|---|---|
| CPU | AMD Ryzen 7 7800X3D — 8C/16T, 96 MB L3 V-Cache, 4.2 GHz base / 5.0 GHz boost, Zen 4 |
| Memory | 64 GB DDR5-6000 CL30 (2×32 GB), EXPO, dual-channel |
| Storage | 1× 2 TB PCIe 4.0 NVMe (WD Black SN850X) + 1× 4 TB SATA SSD for datasets |
| Power | Corsair RM850x — 850 W 80+ Gold, fully modular, ATX 3.1 |
| Software | Ubuntu 24.04 LTS · CUDA 12.8 · PyTorch 2.7 · vLLM |
On price. Part costs move week to week and the right spec
depends on what you run, so a published number would be out of date and
probably wrong for you. Tell us the workload and what you have to spend and
you get an itemised quote — parts at cost, build fee listed
separately, nothing hidden in the bill of materials.
The other designs
Three starting points, each sized against a model it has to hold. If none of them is the right fit we adjust the spec to what you actually plan to run.
Get a build quoted.
Tell us the model, the data and the constraint. We will come back with a spec and an itemised price.
Start a project