# Dankserver System Specs

## Server Overview

Dankserver is an NVIDIA GPU server for vLLM inference. The host runs Ubuntu 24.04 with an RTX 3090 and 62 GB of system RAM.

## Hardware Specifications

### CPU

| Property | Value |
|----------|-------|
| Architecture | x86_64 |
| Vendor | AuthenticAMD |
| Cores | 8 (1 socket) |
| NUMA Nodes | 1 (node 0, 63503 MB) |

### GPU

| Property | Value |
|----------|-------|
| Model | NVIDIA GeForce RTX 3090 |
| VRAM | 24576 MiB (24 GB) |
| Driver | 595.84 |
| CUDA Version | 13.2 |
| CUDA Toolkit | 12.0 (nvcc) |

### Memory

| Property | Value |
|----------|-------|
| System RAM | 62 GiB |
| Swap | 127 GiB |
| /dev/shm | 32 GiB |

### Storage

| Filesystem | Size | Used | Avail | Use% |
|------------|------|------|-------|------|
| / (nvme0n1p2) | 915G | 849G | 20G | 98% |
| /mnt/entropy (dm-0) | 91T | 86T | 977G | 99% |

### OS and Software

| Property | Value |
|----------|-------|
| OS | Ubuntu 24.04.4 LTS (Noble Numbat) |
| Kernel | 7.0.0-28-generic |
| Python | 3.12.3 |

### Active Services

A llama-server process occupies approximately 20 GB of the RTX 3090 VRAM.

## VLLM Relevance

- 24 GB VRAM limits model size. Use FP8 quantization for large models.
- 62 GB system RAM provides ample swap space for KV cache offloading.
- 127 GB swap supports large `--swap-space` values for CPU KV cache paging.
- Root disk has only 20 GB free. Store models on /mnt/entropy.
- CUDA 12.0 and Python 3.12.3 are compatible with vLLM.

## See Also

- [[VLLM Overview]]
- [[Hybrid CPU GPU Processing Dankserver]]
- [[RAM CPU Offloading in VLLM]]
- [[Running Qwen3.6 35B A3B FP8 on Dankserver]]