Frank
219a097b39
Every payload swap a live endpoint has ever run is now one row in that endpoint's Eras table, with its rollback path in the same row. No per-attempt page, no per-swap ledger, nowhere else. - Added: LLM/frank-archon.md (radiance, 2x R9700 TP=2), LLM/frank-dragoon.md (halogen flash-server, 19 eras), LLM/frank-zealot.md (llama.cpp PrismML fork on the 3090). Each carries Current shape, Eras, Laws, wire contract, files. - Deleted: 45 per-payload runbooks -- the frank-dragoon line (11 including the pre-name halogen/kingjones/kairic/CIRU/eemin/agentionai/dflash2 pages and the benchmark page), the frank-zealot line (llama.cpp/vLLM/ik_llama/SGLang eras), the frank-archon line (vLLM/FreeToken/R9V/llama.cpp/radiance eras), plus frank-medium, frank-npu and the ubatch/PCIe one-offs that owned nothing. - Rewired: every wikilink and markdown-path reference to a folded page points at the endpoint page instead; the three Research see-also lists and the ubatch sweep's runbook link included. No anchored links existed in the set. - Regenerated both index pages as pure locators -- one row, one clause, no numbers -- so the docs_completeness locator law holds for all 153 pages. tests/docs_completeness.bats green: index links every page, no unresolved links. The pages moved to .AGENTTRASH/20261018-doc-dedupe/LLM/ (gitignored, and git history holds every byte).
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type, description, tags, timestamp
| type | description | tags | timestamp | ||
|---|---|---|---|---|---|
| reference | This index contains all documentation for vLLM deployment on Dankserver and Dankclaw. |
|
2026-08-28 |
vLLM Index
RETIRED (2026-08-18). The vLLM service on Dankclaw was replaced by the CIRU ROCmFPX llama.cpp runtime (v3). These pages are historical reference. See frank-dragoon.
Documentation Overview
This index contains all documentation for vLLM deployment on Dankserver and Dankclaw.
Hardware Guides
- Dankserver System Specs — NVIDIA GPU server specifications
- Dankclaw System Specs — AMD GPU server specifications
vLLM Architecture
- VLLM Overview — Complete vLLM documentation including installation, CLI, API, and key arguments
- RAM CPU Offloading in VLLM — CPU RAM offloading mechanisms, swap space, and memory configuration
- Hybrid CPU GPU Processing Dankserver — NVIDIA GPU with system RAM hybrid processing
- Shared Memory Architecture Dankclaw — AMD ROCm unified memory and APU configuration
Model Deployment Guides
- Running Qwen3.6 35B A3B FP8 on Dankserver — Qwen3.6-35B-A3B FP8 deployment on NVIDIA GPU
- Running Qwen3.6 27B FP8 on Dankclaw — Qwen3.6-27B FP8 deployment on AMD GPU
Quick Reference
Installation Commands
# NVIDIA GPU
uv pip install vllm --torch-backend=auto
# AMD ROCm
uv pip install vllm --extra-index-url https://wheels.vllm.ai/rocm/
# CPU
uv pip install vllm --extra-index-url https://wheels.vllm.ai/nightly/cpu/
Server Start Commands
# Basic server
vllm serve Qwen/Qwen2.5-1.5B-Instruct
# With tensor parallelism
vllm serve meta-llama/Llama-3.1-70B-Instruct --tensor-parallel-size 4
# With quantization
vllm serve Qwen/Qwen2.5-1.5B-Instruct --quantization fp8
# With GPU memory control
vllm serve Qwen/Qwen2.5-1.5B-Instruct --gpu-memory-utilization 0.8 --swap-space 8
Common API Endpoints
| Endpoint | Method | Description |
|---|---|---|
| /v1/models | GET | List available models |
| /v1/completions | POST | Text completion |
| /v1/chat/completions | POST | Chat completion |
| /health | GET | Health check |
| /metrics | GET | Prometheus metrics |
Key Parameters
| Parameter | Description | Typical Value |
|---|---|---|
| tensor_parallel_size | Number of GPUs for model sharding | 1-8 |
| gpu_memory_utilization | Fraction of GPU memory for KV cache (default 0.92) | 0.7-0.95 |
| swap_space | Removed in current vLLM; use --kv-offloading-size |
n/a |
| max_model_len | Maximum context length | auto |
| max_num_batched_tokens | Max tokens per batch | 2048-8192 |
| max_num_seqs | Max sequences per batch | 128-512 |
Quantization Methods
| Method | GPU Support | Description |
|---|---|---|
| FP8 | Hopper, Ada (native); Ampere W8A16 via Marlin; RDNA via emulation | FP8 E4M3 inference |
| INT8 | Most GPUs | Weight-only INT8 |
| GPTQ | Most GPUs (NVIDIA; limited on ROCm) | Post-training GPTQ |
| AWQ | Turing+ (NVIDIA) | Activation-aware weight quantization |
| GGUF | CPU, GPU | General GPU unification format |