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Frank 35c44c4123 docs+deploy: Dankserver now llama.cpp frank-default-small (HauhauCS Q6_K_P + DFlash)

Retire vllm-awq-qwen36 (AWQ) from target maps, README, deployment, KB index,
Dankserver specs, DFlash and FP8 docs. New dankserver runtime: upstream
llama.cpp, port 7770, alias frank-default-small, 3x262144 ctx, DFlash Q8_0
draft, MoE experts offloaded to CPU, attention+KV on GPU (K q8_0, V f16).
deploy.sh now maps dankserver to frank-default-small and symlinks its unit.
models.json: dankserver baseUrl -> :7770, contextWindow -> 262144.

2026-08-11 01:18:29 -07:00

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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
Model	AMD Ryzen 7 7700X
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	729G	140G	84%
/mnt/entropy (dm-0)	91T	86T	910G	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

The active frank-default-small service (llama.cpp, b10108+) serves the HauhauCS Qwen3.6-35B-A3B uncensored Q6_K_P model on port 7770 with a DFlash draft. It runs 3 parallel slots at 262144 context each. All 40 layers' MoE expert weights sit on CPU (--n-cpu-moe 40) while non-expert tensors and the full-attention KV cache stay on GPU (--gpu-layers all, KV K=q8_0, V=f16). At load it uses about 22 GB of the 24 GB VRAM and roughly 4 GB of resident RAM (experts are lazy-mapped).

Hardware Relevance

24 GB VRAM limits the GPU-resident footprint. With 3 x 262144 context, the full-attention KV cache plus non-expert weights consume about 22 GB, leaving about 2 GB of headroom. MoE experts must stay on CPU.
62 GB system RAM holds the ~29 GB of MoE expert weights with room to spare (~57 GB available after load).
127 GB swap is available for CPU KV cache paging if GPU KV offload is disabled.
Root disk has approximately 140 GB free. Store the GGUF models under /home/dank/models (about 32 GB total).

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