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
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vLLM Scripts — Knowledge Base
Documentation for running vLLM inference on two local machines.
Deployment Topology
graph LR
subgraph Dankserver[NVIDIA Dankserver - Ubuntu 24.04]
A[RTX 3090 24GB + 62GB RAM]
B[vLLM 0.26.0 in Podman\nvllm-qwen36-dflash]
C[Qwen3.6-35B-A3B-FP8\n+ DFlash draft, port 8000]
A --> B --> C
end
subgraph Dankclaw[AMD Strix Halo - Ubuntu 26.04]
D[gfx1151 APU 30GiB phys / 96GiB GPU-visible]
E[ROCmFPX llama.cpp\n/ROCmFPX/build-strix-rocmfp4]
F[Ling-3.0-flash ROCmFP4-MTP\ndraft-mtp, port 8080]
D --> E --> F
end
G[LLM Clients / API] -->|HTTP :8000| B
G -->|HTTP :8080| E
Servers
| Server | GPU | VRAM / Memory | OS |
|---|---|---|---|
| Dankserver System Specs | NVIDIA RTX 3090 | 24 GB VRAM, 62 GB RAM | Ubuntu 24.04 |
| Dankclaw System Specs | AMD Radeon 8060S (Strix Halo) | 30 GiB physical / 96 GiB GPU-visible | Ubuntu 26.04 |
vLLM Reference
- VLLM Overview — installation, CLI, API, architecture, quantization, parallelism
- VLLM Index — quick reference with commands, endpoints, and parameter table
Memory Management
- RAM CPU Offloading in VLLM — KV cache swap between GPU VRAM and system RAM
- Hybrid CPU GPU Processing Dankserver — NVIDIA GPU compute with system RAM offload
- Shared Memory Architecture Dankclaw — AMD unified memory and ROCm configuration
Model Deployment
- Running Qwen3.6 35B A3B FP8 on Dankserver — MoE model (35B total, 3B active) on RTX 3090
- Running Qwen3.6 27B FP8 on Dankclaw — Dense model (27B) on Strix Halo APU