TinkerLab
ARTIFACT // DEPLOY-WORKSTATION-96GB-OR-R9700.SH (SH)

RTX PRO 6000 Blackwell (96GB Max-Q/600W) & Radeon AI PRO R9700 (32GB) Tuner (deploy-workstation-96gb-or-r9700.sh)

Applies 300W Max-Q or 450W sweet-spot power cap on RTX PRO 6000 Blackwell (96GB GDDR7 ECC), or configures ROCm/Vulkan flags for single/dual AMD Radeon AI PRO R9700 (32GB/64GB).

[KEY VERIFIED TAKEAWAY / TL;DR]This reproducible configuration artifact "RTX PRO 6000 Blackwell (96GB Max-Q/600W) & Radeon AI PRO R9700 (32GB) Tuner" (deploy-workstation-96gb-or-r9700.sh, SH) is paired with Tinker AI Lab's hardware-verified guide "rtx-pro-6000-blackwell-96gb-vs-radeon-ai-pro-r9700-32gb-workstation-llm-benchmark". It exposes 3 customizable browser variables (BLACKWELL_WATTS=300, TARGET_MODEL=Qwen/Qwen3-Next-80B-A3B-Instruct-FP8, MAX_CTX_LEN=65536) with loopback-first security defaults.
01 // HOMELABLocal AI / HomeLab· Verified: 2026-11-02
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deploy-workstation-96gb-or-r9700.sh

RTX PRO 6000 Blackwell (96GB Max-Q/600W) & Radeon AI PRO R9700 (32GB) Tuner

Applies 300W Max-Q or 450W sweet-spot power cap on RTX PRO 6000 Blackwell (96GB GDDR7 ECC), or configures ROCm/Vulkan flags for single/dual AMD Radeon AI PRO R9700 (32GB/64GB).

View Paired Guide →
Customizable Variables (Saved in Browser)
UTF-8 Encoded · Live Client-Side Compilation
#!/usr/bin/env bash
# Tinker AI — RTX PRO 6000 Blackwell (96GB) & Radeon AI PRO R9700 (32GB) Launcher (Guide #30)
set -euo pipefail

WATTS="300"
MODEL="Qwen/Qwen3-Next-80B-A3B-Instruct-FP8"
CTX="65536"

if command -v nvidia-smi >/dev/null 2>&1; then
  echo "=== [NVIDIA RTX PRO 6000 Blackwell 96GB] Applying $WATTS W Power Profile & Checking ECC ==="
  sudo nvidia-smi -pm 1
  sudo nvidia-smi -pl "$WATTS"
  nvidia-smi --query-gpu=name,memory.total,ecc.mode.current,power.draw,power.limit --format=csv
  exec vllm serve "$MODEL" \
    --max-model-len "$CTX" \
    --gpu-memory-utilization 0.92 \
    --kv-cache-dtype fp8 \
    --enable-prefix-caching \
    --port 8000
else
  echo "=== [AMD Radeon AI PRO R9700 32GB RDNA 4 (gfx1201)] Configuring ROCm / Vulkan Stack ==="
  unset HSA_OVERRIDE_GFX_VERSION
  export HSA_ENABLE_SDMA=0
  export NCCL_IB_DISABLE=1
  export NCCL_P2P_LEVEL=PHB
  rocm-smi --showproductname --showmeminfo vram || vulkaninfo --summary | grep -i "deviceName"
  echo "Ready for ROCm vLLM or llama-server Vulkan RADV (-ngl 99 -fa -ctk q8_0 -ctv q8_0 -c $CTX)."
fi
PARAMETER SPECIFICATION // 参数化变量规范说明表

Customizable Parameter Reference for deploy-workstation-96gb-or-r9700.sh

This SH artifact exposes 3 template variables compiled client-side in your browser.

Template TokenParameter DescriptionVerified DefaultExample Format
{{BLACKWELL_WATTS}}RTX PRO 6000 Power Cap (Watts: 300 Max-Q / 450 / 600)300300
{{TARGET_MODEL}}Model Path or HuggingFace RepoQwen/Qwen3-Next-80B-A3B-Instruct-FP8Qwen/Qwen3-Next-80B-A3B-Instruct-FP8
{{MAX_CTX_LEN}}Context Window (Tokens)6553665536
PAIRED HARDWARE MANIFEST // 配套实测环境与边界记录

Verified Environment for "Workstation Local LLM Showdown: NVIDIA RTX PRO 6000 Blackwell (96GB GDDR7 · 300W Max-Q vs 600W) vs AMD Radeon AI PRO R9700 (32GB / Dual 64GB RDNA 4)"

Tested Hardware & OS

Host A: NVIDIA RTX PRO 6000 Blackwell (96GB GDDR7 ECC · 1,792 GB/s · sm_120) | Host B: 2x AMD Radeon AI PRO R9700 (32GB GDDR6 each = 64GB · 640 GB/s · RDNA 4 gfx1201)

Pinned Stack & Model Versions
vLLM 0.8.2 (CUDA 12.8 FP8/NVFP4 + MTP & ROCm 6.4)llama.cpp b4780 (CUDA sm_120 / Vulkan RADV / HIP)Ollama 0.6.2
Offline Boundary (100% Local Workstation Execution (ECC Verified))

All vLLM and llama.cpp benchmarks run locally offline with hardware ECC enabled on RTX PRO 6000 Blackwell.

Known Operational Limits & Failure Modes
  • Enabling GDDR7 ECC on RTX PRO 6000 Blackwell reserves ~4.5 GB of physical memory for inline parity metadata, leaving 91.5 GB of usable VRAM in `nvidia-smi`.
  • On AMD Radeon AI PRO R9700 (32GB `gfx1201`), `llama.cpp` Vulkan (`RADV`) decodes sparse MoE models (`Qwen3-30B-A3B`) 28% faster than ROCm HIP, whereas ROCm HIP processes dense 8K prompts 1.7x faster than Vulkan.
DEPLOYMENT CHECKLIST // 配置落地核验步骤

3-Step Verification Checklist After Deploying deploy-workstation-96gb-or-r9700.sh

  1. Verified usable VRAM (91.5 GB with ECC on) and set persistent power cap (`sudo nvidia-smi -pl 300` or `450`) on RTX PRO 6000 Blackwell.
  2. Tested `llama-server` with Mesa 25.0+ Vulkan (`RADV`) on Radeon AI PRO R9700 for sparse MoE models (>100 tok/s on Qwen3-30B-A3B).
  3. Exported `HSA_ENABLE_SDMA=0` and `iommu=pt` when scaling across 2x Radeon AI PRO R9700 (64GB) cards.