3a64c8f3dd2640469e2267f17e1095e671942900
Correct stale and incorrect facts after exhaustive verification: - Dankclaw: NUMA node 0 = 31213 MB; disk 661G/1.1T/38%; vLLM 0.26.0 in /home/dank/vllm-rocm-venv (not vllm-env); clarify 96 GiB GPU-visible is a driver overcommit ceiling over 30 GiB physical (confirmed via sysfs mem_info_vram_total=103079215104) - Dankserver: disk 729G/140G free/84%; /mnt/entropy 910G free; active service is vLLM EngineCore (22 GB), not llama-server; CPU model Ryzen 7 7700X - index.md: Dankclaw 30GiB phys / 96GiB GPU-visible (was '61 GB unified'); add deployment topology mermaid diagram - vLLM defaults (from source): gpu_memory_utilization=0.92, max_num_seqs=128, swap_space removed (now --kv-offloading-size) across Overview/Index/RAM/Hybrid - Quantization: FP8 not native on Ampere (RTX 3090) or RDNA 3.5 (gfx1151); add per-model hardware quantization notes; AWQ/GPTQ limited on ROCm - Speculative decoding: add DFlash, DSpark, MTP, EAGLE3 to feature list - Confirm Qwen3.6-27B and Qwen3.6-35B-A3B specs are correct (HF-verified) - Production note: Dankclaw primary llama.cpp service runs ROCmFPX Ling-3.0-flash RocmFP4 MTP, not vLLM Qwen3.6-27B
vLLM Scripts
Scripts for running large language models via vLLM on two local machines.
Targets
| Host | User | Codename | Architecture |
|---|---|---|---|
| dankserver | dank | DankServer | NVIDIA GPU + System RAM |
| dankclaw | dank | DankClaw | AMD Strix Halo (Shared Memory) |
Models
| Model | Target | Format |
|---|---|---|
| Qwen3.6 35B A3B FP8 | dankserver | FP8 |
| Qwen3.6 27B FP8 | dankclaw | FP8 |
Structure
docs/— Project knowledge base with research notes on vLLM configuration, hardware specifics, and deployment notesscripts/— Executable vLLM launch scripts (coming soon)
Knowledge Base
See docs/README.md for the project knowledge base index.
Languages
Shell
60.4%
Python
21%
HTML
6.2%
Jinja
3.9%
C++
3.9%
Other
4.6%