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

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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.
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Frank
2026-08-11 01:18:29 -07:00
parent 6a86a9df93
commit 35c44c4123
8 changed files with 34 additions and 32 deletions
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AGENTS.md
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## Overview
This project manages deployment scripts for two LLM inference servers. Both run vLLM. Dankclaw runs a vLLM-ROCm service for Ling-3.0-flash (CIRU INT4). Dankserver runs a vLLM service for Qwen3.6. See [docs/deployment.md](docs/deployment.md) for the full deployment and update process.
This project manages deployment scripts for two LLM inference servers. Dankclaw runs a vLLM-ROCm service for Ling-3.0-flash (CIRU INT4). Dankserver runs a llama.cpp service for Qwen3.6-35B-A3B (HauhauCS uncensored Q6_K_P) with a DFlash draft and CPU-offloaded MoE experts. See [docs/deployment.md](docs/deployment.md) for the full deployment and update process.
## Git Workflow
@@ -23,7 +23,7 @@ Use `scripts/deploy.sh` to deploy committed changes to a target. It pushes `main
```
./scripts/deploy.sh dankclaw # vLLM (frank-default-large, port 7770)
./scripts/deploy.sh dankserver # vLLM (vllm-awq-qwen36, port 34401)
./scripts/deploy.sh dankserver # llama.cpp (frank-default-small, port 7770)
./scripts/deploy.sh dankclaw --dry-run # preview without changes
```
@@ -43,7 +43,7 @@ Target map:
| Target | Host | Runtime | Service | Port |
|--------|------|---------|---------|------|
| Dankclaw | dank@dankclaw | vLLM-ROCm (CIRU INT4) | frank-default-large | 7770 |
| Dankserver | dank@dankserver | vLLM (Docker) | vllm-awq-qwen36 | 34401 |
| Dankserver | dank@dankserver | llama.cpp (Q6_K_P + DFlash, MoE offload) | frank-default-small | 7770 |
## Why
README.md
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| Service | Host | Runtime | Model | Port |
|---------|------|---------|-------|------|
| frank-default-large | dankclaw | vLLM-ROCm (CIRU) | Ling-3.0-flash CIRU INT4 MTP | 7770 |
| vllm-awq-qwen36 | dankserver | vLLM (Docker) | Qwen3.6-35B-A3B AWQ 4-bit | 34401 |
| frank-default-small | dankserver | llama.cpp (DFlash) | Qwen3.6-35B-A3B uncensored Q6_K_P | 7770 |
> The retired ROCmFPX llama.cpp service on Dankclaw was replaced by the vLLM service above. Its unit file `scripts/llama-server.service` remains for reference.
> The retired ROCmFPX llama.cpp service on Dankclaw was replaced by the vLLM service above. The retired `vllm-awq-qwen36` (AWQ 4-bit) service on Dankserver was replaced by the llama.cpp service above. Legacy unit files remain in `scripts/` for reference.
## Models
| Model | Target | Format |
|-------|--------|--------|
| Ling-3.0-flash CIRU INT4 (MTP) | dankclaw | INT4 W4A16 (Quark/vLLM) |
| Qwen3.6 35B A3B AWQ 4bit | dankserver | AWQ |
| Qwen3.6 35B A3B uncensored Q6_K_P (DFlash draft) | dankserver | GGUF Q6_K_P (llama.cpp, MoE offload) |
| Qwen3.6 35B A3B AWQ 4bit | dankserver | AWQ (retired) |
| Qwen3.6 35B A3B FP8 | dankserver | FP8 (documented, not active) |
| Qwen3.6 27B FP8 | dankclaw | FP8 (documented, not active) |
## Structure
- `docs/` — Project knowledge base with research notes on vLLM configuration, hardware specifics, speculative decoding, and deployment notes
- `scripts/` — Deployment and launch scripts (deploy.sh, serve-vllm-qwen36-dflash.sh, validate-vllm.sh, systemd unit files)
- `scripts/` — Deployment and launch scripts (deploy.sh, serve-llama-frank-small.sh, serve-ling3-vllm.sh, systemd unit files)
## Deployment
docs/DFlash DSpark Speculative Decoding.md
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## Deployment on Dankserver (NVIDIA RTX 3090)
Dankserver runs vLLM in a Podman container with the RTX 3090. The RTX 3090 is Ampere (compute capability 8.6). Use these conditions:
The active Dankserver deployment runs **llama.cpp + DFlash** (`frank-default-small`), not vLLM. It serves the HauhauCS Qwen3.6-35B-A3B uncensored `Q6_K_P` on port 7770 with the `Alittlehammmer/Qwen3.6-35B-A3B-DFlash` Q8_0 draft, 3 slots at 262144 context, and MoE experts on CPU. See [[deployment]] and `scripts/serve-llama-frank-small.sh`.
The vLLM material below documents the archived AWQ/DFlash path on the same hardware. The RTX 3090 is Ampere (compute capability 8.6). Use these conditions:
- FP8 KV cache is valid on CUDA 12.
- FP8 weights compute through a fallback path; no native FP8 tensor cores.
docs/Dankserver System Specs.md
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### Active Services
A vLLM engine core (Podman container `vllm-qwen36-dflash`) occupies approximately 22 GB of the RTX 3090 VRAM (`nvidia-smi` reports `VLLM::EngineCore` at 22164 MiB).
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).
## vLLM Relevance
## Hardware 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 approximately 140 GB free. Store models on /mnt/entropy.
- CUDA 12.0 and Python 3.12.3 are compatible with vLLM.
- 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).
## See Also
docs/Running Qwen3.6 35B A3B FP8 on Dankserver.md
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### Active Service Conflict
A vLLM engine core (Podman container `vllm-qwen36-dflash`) occupies roughly 22 GB of the 24 GB VRAM. Stop it before starting a competing service:
The active `frank-default-small` service (llama.cpp, port 7770) uses about 22 GB of the 24 GB VRAM. The retired `vllm-awq-qwen36` (Podman, ~22 GB) and `vllm-qwen36` services are not active. Stop any competing service before starting another:
```
podman stop vllm-qwen36-dflash
docs/deployment.md
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@@ -9,7 +9,7 @@ Two servers run LLM inference services. Each server pulls its scripts from this
| Target | Host | Runtime | Service | Port |
|--------|------|---------|---------|------|
| Dankclaw | dank@dankclaw | vLLM-ROCm (CIRU INT4) | frank-default-large | 7770 |
| Dankserver | dank@dankserver | vLLM (Docker) | vllm-awq-qwen36 | 34401 |
| Dankserver | dank@dankserver | llama.cpp (Q6_K_P + DFlash, MoE offload) | frank-default-small | 7770 |
## Workflow
@@ -90,9 +90,10 @@ Run these commands on Dankserver:
```
cd /home/dank/vLLM
git pull origin main
sudo ln -sf /home/dank/vLLM/scripts/frank-default-small.service /etc/systemd/system/frank-default-small.service
sudo systemctl daemon-reload
sudo systemctl restart vllm-qwen36
curl -sf http://127.0.0.1:8000/health
sudo systemctl restart frank-default-small
curl -sf http://127.0.0.1:7770/health
```
## Service Units
@@ -101,11 +102,11 @@ curl -sf http://127.0.0.1:8000/health
The active service on Dankclaw runs a vLLM-ROCm runtime for the Ling-3.0-flash CIRU INT4 (W4A16) model. It serves under the alias `frank-default-large` on port 7770 with native MTP speculative decoding. The unit file is `scripts/frank-default-large.service` in the repository. The machine symlinks it to `/etc/systemd/system/frank-default-large.service`. The service launches through `scripts/serve-ling3-vllm.sh`, which sources the CIRU runtime and passes the production settings (host `0.0.0.0`, port 7770, gpu memory utilization 0.95).
### Dankserver — vllm-awq-qwen36
### Dankserver — frank-default-small
The active vLLM service on Dankserver runs in a Podman/Docker container and serves the Qwen3.6-35B-A3B AWQ 4-bit model on port 34401. The unit file is a physical file on the machine, not a symlink into the repository.
The active service on Dankserver runs llama.cpp (upstream, `b10108+`) and serves the HauhauCS Qwen3.6-35B-A3B uncensored `Q6_K_P` model under the alias `frank-default-small` on port 7770. It uses a DFlash draft (`Alittlehammmer/Qwen3.6-35B-A3B-DFlash:Q8_0`) with `--spec-draft-n-max 7`, 3 parallel slots at 262144 context each, and mmproj vision. All 40 layers' MoE experts stay on CPU (`--n-cpu-moe 40`) with non-expert tensors on GPU (`--gpu-layers all`); the full-attention KV cache stays on GPU with K quantized to `q8_0` and V at `f16`. The unit file is `scripts/frank-default-small.service`, symlinked to `/etc/systemd/system/`. It launches through `scripts/serve-llama-frank-small.sh`, which reads tunables from `scripts/frank-default-small.env`.
> Note: the failed `vllm-qwen36.service` (FP8) and the retired `llama-server.service` (ROCmFPX llama.cpp) are not active. Verify the intended service before a restart. See the repository `git log` for the latest decision.
> Note: this service replaced the retired `vllm-awq-qwen36` (AWQ 4-bit, port 34401) and the earlier `vllm-qwen36` (FP8) / `llama-server` (ROCmFPX) units. The repo tracks `main` on Dankserver at `/home/dank/vLLM`.
## Validation
docs/index.md
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graph LR
subgraph Dankserver[NVIDIA Dankserver - Ubuntu 24.04]
A[RTX 3090 24GB + 62GB RAM]
B[vLLM in Podman
vllm-awq-qwen36]
C[Qwen3.6-35B-A3B AWQ 4bit
port 34401]
B[llama.cpp DFlash
frank-default-small]
C[Qwen3.6-35B-A3B uncensored Q6_K_P
experts on CPU, port 7770]
A --> B --> C
end
@@ -24,7 +24,7 @@ port 7770]
D --> E --> F
end
G[LLM Clients / API] -->|HTTP :34401| B
G[LLM Clients / API] -->|HTTP :7770| B
G -->|HTTP :7770| E
```
scripts/deploy.sh
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#
# Targets:
# dankclaw - vLLM-ROCm server (frank-default-large.service, port 7770)
# dankserver - vLLM server (vllm-awq-qwen36.service, port 34401)
# dankserver - llama.cpp server (frank-default-small.service, port 7770)
#
# Example:
# ./deploy.sh dankclaw
@@ -34,8 +34,8 @@ SERVICE_HEALTH[dankclaw]="http://127.0.0.1:7770/health"
REMOTE_USER[dankserver]=dank
REMOTE_HOST[dankserver]=dankserver
REMOTE_DIR[dankserver]="/home/dank/vLLM"
SERVICE[dankserver]="vllm-awq-qwen36"
SERVICE_HEALTH[dankserver]="http://127.0.0.1:34401/health"
SERVICE[dankserver]="frank-default-small"
SERVICE_HEALTH[dankserver]="http://127.0.0.1:7770/health"
TARGET="${1:-}"
DRY_RUN=0
@@ -106,8 +106,7 @@ case '${TARGET}' in
sudo ln -sf '${REMOTE_DIR[$TARGET]}/scripts/frank-default-large.service' /etc/systemd/system/frank-default-large.service
;;
dankserver)
# vllm-qwen36.service is a physical file; no symlink needed.
:
sudo ln -sf '${REMOTE_DIR[$TARGET]}/scripts/frank-default-small.service' /etc/systemd/system/frank-default-small.service
;;
esac