RTX 5090 Qwen3.8-27B dsh 全套實測：自寫推理引擎 NInfer × DeepSeek Harness × 開源編碼 agent 任務 —— 跑 13 小時真實編程任務的數據、6 個坑、以及「並發不是越大越快」
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啟動腳本︰
# ninfer-serve.sh #!/bin/bash # NInfer host control: ninfer-serve.sh start | stop | status # Binary reports usage.prompt_tokens_details.cached_tokens (OpenAI chat-completions), # so DSH shows real KV prefix cache hit % instead of 0%. # Default = text-only at 262K context (full int8 KV pool, ~10.45 GiB). # Vision is optional: VISION=1 ninfer-serve.sh start switches to 192K context + --vision # with media buffers trimmed from defaults (1G+2G) to 256M+512M so the fixed Vision # buffers fit the ~10.4 GiB free after weights on the 5090 (at 262K they do not). # C=2: median agent prompt scales to ~86K at 192K; two frontiers (~172K) fit the pool, # so requests reuse their frontier (97-99% cached). set -u PORT=18080 LOG=/home/user/ninfer_serve.log APP=/home/user/ninfer-build/apps/ninfer-serve ART=/home/user/ninfer_artifacts/qwen3_8_27b_nvfp4.ninfer if [ "${VISION:-0}" = "1" ]; then CTX=196608 VISION_FLAGS="--vision --media-cache-mib 256 --media-live-mib 512" else CTX=262144 VISION_FLAGS="" fi is_running() { pgrep -f "ninfer-serve.*qwen3_8_27b" >/dev/null 2>&1; } case "${1:-start}" in start) if is_running; then echo "already running (pid $(pgrep -of 'ninfer-serve.*qwen3_8_27b'))" exit 0 fi export LD_LIBRARY_PATH=/home/user/ninfer_deps/prefix/usr/lib/x86_64-linux-gnu:${LD_LIBRARY_PATH:-} cd /home/eason || exit 1 setsid nohup "$APP" "$ART" \ --host 0.0.0.0 --port $PORT --device 0 \ --max-context $CTX --prefill-chunk 1024 --kv-dtype int8 \ $VISION_FLAGS \ --max-concurrency 2 --pending-timeout-ms 600000 \ --spec mtp --draft-tokens 3 --lm-head-draft >>"$LOG" 2>&1 & for i in $(seq 1 30); do sleep 5 if curl -s http://127.0.0.1:$PORT/health | grep -q ok; then echo "NInfer up: pid $(pgrep -of 'ninfer-serve.*qwen3_8_27b'), ctx=$CTX vision=${VISION:-0}, log $LOG" exit 0 fi done echo "server did not become healthy in 150s; last log lines:"; tail -5 "$LOG"; exit 1 ;; stop) if ! is_running; then echo "not running"; exit 0; fi pkill -f "ninfer-serve.*qwen3_8_27b" for i in $(seq 1 10); do sleep 2; is_running || break; done if is_running; then echo "still running (try: fuser -k $PORT/tcp)"; exit 1; fi echo "stopped" ;; status) if is_running; then echo "running pid $(pgrep -of 'ninfer-serve.*qwen3_8_27b')"; curl -s http://127.0.0.1:$PORT/health; echo else echo "not running" fi ;; *) echo "usage: $0 start|stop|status (VISION=1 for vision mode)"; exit 2;; esac記得把
{ip}換掉:: start.bat @echo off setlocal title NInfer Start rem --- self-elevate (netsh portproxy + firewall need admin) --- net session >nul 2>&1 if %errorlevel% neq 0 ( echo Requesting administrator rights... powershell -NoProfile -Command "Start-Process '%~f0' -Verb RunAs" exit /b ) echo [1/4] Starting NInfer server in WSL Ubuntu (port 18080, MTP3 on)... wsl -d Ubuntu -- bash /mnt/c/Users/user/Desktop/ninfer-serve.sh start if errorlevel 1 goto :fail for /f "usebackq" %%i in (`wsl -d Ubuntu -- hostname -I`) do set WSL_IP=%%i echo [2/4] Repairing LAN portproxy: 0.0.0.0:18080 -> %WSL_IP%:18080 ... netsh interface portproxy delete v4tov4 listenaddress=0.0.0.0 listenport=18080 >nul 2>&1 netsh interface portproxy add v4tov4 listenaddress=0.0.0.0 listenport=18080 connectaddress=%WSL_IP% connectport=18080 echo [3/4] Ensuring firewall rule ... powershell -NoProfile -Command "if (-not (Get-NetFirewallRule -DisplayName 'NInfer serve 18080' -ErrorAction SilentlyContinue)) { New-NetFirewallRule -DisplayName 'NInfer serve 18080' -Direction Inbound -Protocol TCP -LocalPort 18080 -Action Allow -Profile Private,Public | Out-Null; Write-Host 'firewall rule added' } else { Write-Host 'firewall rule exists' }" echo [4/4] Verifying via LAN IP ... powershell -NoProfile -Command "try { $r = Invoke-RestMethod -Uri http://{ip}:18080/health -TimeoutSec 8; Write-Host ('LAN OK: ' + ($r | ConvertTo-Json -Compress)) } catch { Write-Host ('LAN FAIL: ' + $_.Exception.Message) }" echo. echo Done. Server URL for other devices: http://{ip}:18080 echo Model qwen3.8-27b (nvfp4), MTP3 on, no vision, KV int8. pause exit /b 0 :fail echo Start failed - check WSL log: wsl -d Ubuntu -- tail -20 /home/eason/ninfer_serve.log pause -
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学习了，本地模型新入坑小白，跟大神学习。
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Windows 原生能不能比 WSL 快，先分两句说：
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瓶颈不同。WSL2 的 CUDA 走 /dev/dxg，GPU kernel 本身接近原生，吃亏的主要是 host
device 的拷贝、pinned memory 和 WSL 的 VM 内存回收抖动，对 prefill 重、并发高的负载更明显。Windows 原生没有这层虚拟化，但受 WDDM 调度影响（消费卡只能用 WDDM，不能切 TCC），长 prefill/大 kernel 要防 TDR 超时重置，把 TdrDelay 调大一点更稳。 -
别只比 decode。你这个场景 agent 负载基本是 prefill 主导，和 1228 楼里那个 98.6% prefill 的结论一致——要比就固定同一组参数（--max-context / --kv-dtype / --spec mtp / --draft-tokens / 并发）分别跑，prefill tok/s 和 decode tok/s 分开记，单看 decode 会误判。
实操上注意：CUDA runtime 与驱动版本要对齐；Windows 高性能电源计划、关掉硬件加速 GPU 计划（HAGS）和后台占用；显存里桌面和其他进程会先吃掉一块，KV capacity 要按实际可用显存留余量。
结论：单卡 27B、prefill 主导的 NInfer 场景，Windows 原生通常能小幅领先 WSL（几个点，配置脏了也可能持平或更差），不是代差。真正的天花板还是 5090 的算力和带宽，选哪个看你现有工具链顺手与否。
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