Download scripts/tbench/tb_server.sh from jaytonde05/kv-cache-quantization-commands: direct link, hf CLI and curl.
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| # vLLM server for one config (runs in its own tmux session). Usage: tb_server.sh CONFIG GPU PORT | |
| # Other models (defaults = Qwen3.8-27B): KVQ_MODEL KVQ_TB_NAME KVQ_REASONING_PARSER, KVQ_SERVE_ARGS adds serve args. | |
| CFG=$1; GPU=$2; PORT=$3 | |
| case $CFG in | |
| BF16) KV=bfloat16; BE=FLASH_ATTN ;; | |
| BF16-FI) KV=bfloat16; BE=FLASHINFER ;; | |
| FP8) KV=fp8_e4m3; BE=FLASH_ATTN ;; | |
| FP4) KV=nvfp4; BE=FLASHINFER ;; | |
| esac | |
| source ~/kvq-env/bin/activate | |
| eval "SERVE_ARGS=(${KVQ_SERVE_ARGS:-})" | |
| mkdir -p ~/tbench/servers | |
| MODEL=${KVQ_MODEL:-~/models/Qwen3.8-27B}; NAME=${KVQ_TB_NAME:-qwen3.8-27b}; RP=${KVQ_REASONING_PARSER:-qwen3} | |
| echo "== vLLM $CFG kv=$KV backend=$BE gpu=$GPU port=$PORT $(date -u)" | |
| CUDA_VISIBLE_DEVICES=$GPU exec vllm serve $MODEL --served-model-name $NAME --port $PORT \ | |
| --dtype bfloat16 --max-model-len 262144 --gpu-memory-utilization 0.90 --reasoning-parser $RP --seed 0 \ | |
| --kv-cache-dtype $KV --attention-backend $BE "${SERVE_ARGS[@]}" 2>&1 | tee -a ~/tbench/servers/${KVQ_TB_LOG_PREFIX:-}$CFG.log | |