Orchestra-Research/AI-Research-SKILLs
tensorrt-llm
Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantization (FP8/INT4), in-flight batching, and multi-GPU scaling.
Before you install
- Last update
- Files in folder
- 4
- Scripts
- No script files found
- SKILL.md size
- 4.9 KB (about 1,260 tokens of context each time it loads)
- License
- MIT
- Source on GitHub
- Orchestra-Research/AI-Research-SKILLs
Skills are plain text instructions the agent follows, sometimes with scripts. Check the source, prefer repositories with many installs and stars, and read any script it ships.
Install
npx skills add Orchestra-Research/AI-Research-SKILLs@tensorrt-llmRuns in a terminal with Node.js 18 or newer. Add -y to skip the prompts and -g to install for every project instead of this one.
Install for your agent
npx skills add Orchestra-Research/AI-Research-SKILLs@tensorrt-llm --agent claude-code -y- Project install writes to
.claude/skills/tensorrt-llm- Global install writes to
~/.claude/skills/tensorrt-llm
Start a new session afterwards so the agent picks the skill up. In Claude Code you can also call it directly with /tensorrt-llm.
What it does
TensorRT-LLM NVIDIA's open-source library for optimizing LLM inference with state-of-the-art performance on NVIDIA GPUs. When to use TensorRT-LLM Use TensorRT-LLM when: - Deploying on NVIDIA GPUs (A100, H100, GB200) - Need maximum throughput (24,000+ tokens/sec on Llama 3) - Require low latency for real-time applications - Working with quantized models (FP8, INT4, FP4) - Scaling across multiple GPUs or nodes Use vLLM instead when: - Need simpler setup and Python-first API - Want PagedAttention without TensorRT compilation - Working with AMD GPUs or non-NVIDIA hardware Use llama.cpp instead…
Excerpt from the skill's own SKILL.md. Read the full file on GitHub before installing: skills run with your agent's permissions.
Categories
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