jetson-llm-benchmark
Benchmark Jetson LLM/VLM serving performance across vLLM, llama.cpp, and Ollama with structured JSON output.
npx skills add NVIDIA/skills --skill jetson-llm-benchmark --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Jetson LLM Benchmark Reproducible Jetson benchmarks with **structured JSON output** so an agent can compare runs. Encodes the workflow from the [Jetson AI Lab GenAI Benchmarking tutorial](https://www.jetson-ai-lab.com/tutorials/genai-benchmarking/). ## Purpose Measure deployed LLM latency and throughput on a Jetson target using the correct runtime-specific benchmark wrapper. Use the JSON output
What does the jetson-llm-benchmark skill do?
Benchmark Jetson LLM/VLM serving performance across vLLM, llama.cpp, and Ollama with structured JSON output.
How do I install it?
Run `npx skills add NVIDIA/skills --skill jetson-llm-benchmark --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From NVIDIA/skills, a repository with 2,789 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.