1Cat-vLLM
Runs large language models (e.g., Qwen3.5 27B/35B) at 4‑bit AWQ precision on Tesla V100 (SM70) GPUs using a custom vLLM build.
- •You have a multi‑GPU V100 cluster and need to serve a 27‑35B model at low latency.
- •You want to cut VRAM usage with 4‑bit AWQ quantization without losing much quality.
- •You need an open‑source alternative to proprietary serving stacks that works with CUDA 12.8.
curl http://localhost:8000/v1/completions \
-H "Content-Type: application/json" \
-d '{"model":"Qwen3.5-27B-AWQ","prompt":"Write a concise 150‑word executive summary for a seed‑stage AI startup.","max_tokens":200,"temperature":0.7}'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/1cat-vllm && curl -fsSL https://workflowstacks.com/api/skills/1cat-vllm/claude-skill -o ~/.claude/skills/1cat-vllm/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/1cat-vllm && curl -fsSL https://workflowstacks.com/api/skills/1cat-vllm/claude-skill -o ~/.claude/skills/1cat-vllm/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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