# VLLM Index ## 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]] -- Qwen3-30B-A3B FP8 deployment on NVIDIA GPU - [[Running Qwen3.6 27B FP8 on Dankclaw]] -- Qwen3-32B 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 | 0.7-0.95 | | swap_space | CPU swap space in GiB | 4-32 | | max_model_len | Maximum context length | auto | | max_num_batched_tokens | Max tokens per batch | 2048-8192 | | max_num_seqs | Max sequences per batch | 128-256 | ### Quantization Methods | Method | GPU Support | Description | |--------|-------------|-------------| | FP8 | Hopper, Ada, Ampere | Native FP8 inference | | INT8 | Most GPUs | Weight-only INT8 | | GPTQ | Most GPUs | Post-training GPTQ | | AWQ | Turing+ | Activation-aware weight quantization | | GGUF | CPU, GPU | General GPU unification format | ## See Also - [[VLLM Overview]] - [[RAM CPU Offloading in VLLM]] - [[Hybrid CPU GPU Processing Dankserver]] - [[Shared Memory Architecture Dankclaw]] - [[Running Qwen3.6 35B A3B FP8 on Dankserver]] - [[Running Qwen3.6 27B FP8 on Dankclaw]]