rtx6kpro: Deploy Massive LLMs on PCIe GPUs without NVLink
From the repo · “RTX 6000 Pro Wiki — Running Large LLMs (Qwen3.5-397B, Kimi-K2.5, GLM-5) on PCIe GPUs without NVLink”
RTX 6000 Pro allows founders to run large language models like Qwen3.5-397B, Kimi-K2.5, and GLM-5 on PCIe GPUs without NVLink, enabling local inference for AI agents
- •You need to deploy large language models on local hardware for data privacy or latency reasons
- •Your AI workflow requires running models like Qwen3.5-397B or Kimi-K2.5 on commodity GPUs
- •You want to test and fine-tune large language models without relying on cloud services
python run_qwen.py --model qwen3.5-397b --gpu 0 --batch-size 32
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Installs with a command or two; your AI agent can do it for you.
mkdir -p ~/.claude/skills/rtx6kpro && curl -fsSL https://workflowstacks.com/api/skills/rtx6kpro/claude-skill -o ~/.claude/skills/rtx6kpro/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
What's inside — free to inspect
Read the entire source before you build — unlike paid marketplaces that hide it behind a buy button.
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Installs with a command or two; your AI agent can do it for you.
mkdir -p ~/.claude/skills/rtx6kpro && curl -fsSL https://workflowstacks.com/api/skills/rtx6kpro/claude-skill -o ~/.claude/skills/rtx6kpro/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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