# vLLM Scripts — Knowledge Base

Documentation for running vLLM inference on two local machines.

## Deployment Topology

```mermaid
graph LR
    subgraph Dankserver[NVIDIA Dankserver - Ubuntu 24.04]
        A[RTX 3090 24GB + 62GB RAM]
        B[llama.cpp ngram-mod
frank-default-small]
        C[Qwen3.6-35B-A3B uncensored Q6_K_P
MoE experts on CPU, port 7770]
        A --> B --> C
    end

    subgraph Dankclaw[AMD Strix Halo - Ubuntu 26.04]
        D[gfx1151 APU 30GiB phys / 96GiB GPU-visible]
        E[llama.cpp --spec-default ngram-mod
frank-default-large]
        F[Qwen3.8-27B UD-Q8_K_XL
Vulkan0 backend, port 7770, PARALLEL=2]
        D --> E --> F
    end

    G[LLM Clients / API] -->|HTTP :7770| B
    G -->|HTTP :7770| E
```

## Servers

| Server                                  | GPU                           | VRAM / Memory                       | OS           |
| --------------------------------------- | ----------------------------- | ----------------------------------- | ------------ |
| [[Dankserver System Specs\|Dankserver]] | NVIDIA RTX 3090               | 24 GB VRAM, 62 GB RAM               | Ubuntu 24.04 |
| [[Dankclaw System Specs\|Dankclaw]]     | 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
- [[deployment]] — deploy and update process for both servers

## 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
- [[frank-default-large-benchmark]] — backend/spec benchmark; chose MTP sidecar (2026-08-14) over DFlash (parallel premature-EOS bug)
- [[qwen3.8-spec-matrix]] — Qwen3.8-27B UD-Q8_K_XL spec matrix; production = --spec-default (ngram-mod), PARALLEL=2, Vulkan0 backend (2026-08-15)
- [[qwen3.8-strix-optimizations]] — Qwen3.8-27B Strix speed research: ranked levers that keep UD-Q8_K_XL (PP to 3090, MTP tuning, same-bit Q8_0 A/B, prefill path, OS), quant landscape, 2026-08-16 test matrix
- [[frank-default-small-benchmark]] — ncmoe and batch/ubatch sweep that drove the Dankserver state
- [[dankserver-vram-growth]] — VRAM/RAM growth investigation behind the recurring cuBLAS crash on frank-default-small
- [[Dankclaw Improvements]] — researched enhancements: self-hosted agentic tools, runtime tuning, server/OS settings
- [[FastFlowLM NPU Inference]] — FastFlowLM (FLM), the AMD NPU-first runtime. The 50 TOPS Strix Halo NPU on Dankclaw: model fit, vendor benchmarks, verified install state, test runbook (2026-08-16)

## Speculative Decoding & Quantization

- [[DFlash DSpark Speculative Decoding]] — block diffusion (DFlash) and semi-autoregressive (DSpark) drafting on vLLM and llama.cpp
- [[Quantization by Hardware Architecture]] — which quant format fits which GPU/CPU

## Pipeline Parallelism

- [[Pipeline Parallelism]] — index of multi-node inference research and sample scripts
  - [[Pipeline Parallelism/llama.cpp RPC]] — ggml-rpc-server + `--rpc` distributed inference
  - [[Pipeline Parallelism/vLLM Pipeline Parallelism]] — vLLM PP across machines
  - [[Pipeline Parallelism/Ethernet Bandwidth Math]] — bytes per token and link feasibility
  - [[Pipeline Parallelism/Mixed-Vendor Experiments]] — NVIDIA + Strix Halo real-world runs
  - [[Pipeline Parallelism/Expected Performance]] — estimated tok/s over 1/2.5/10 GbE
  - [[Pipeline Parallelism/Sample Script Set]] — educational two-node Qwen3.6-27B Q8 split
  - [[Pipeline Parallelism/Qwen3.8 PP Deployment]] — production design + runbook: Qwen3.8-27B head (Strix) / worker (RTX 3090) over RPC, b10433, scripts in scripts/