NVIDIA Model Optimizer is a library that changes deep-learning models through techniques such as quantization, pruning, distillation, neural architecture search, speculative decoding, and sparsity so they can run more efficiently. Developers use it to optimize Hugging Face, PyTorch, or ONNX models and export checkpoints for inference frameworks such as SGLang, TensorRT-LLM, TensorRT, or vLLM. The catalogue entries provide skills, instructions, and a plugin for using its workflows.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/NVIDIA/Model-OptimizerWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/plugins/nvidia/model-optimizer/modelopt)<a href="https://agentmods.dev/plugins/nvidia/model-optimizer/modelopt"><img src="https://agentmods.dev/badge/plugins/nvidia/model-optimizer/modelopt/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/plugins/nvidia/model-optimizer/modelopt"><img src="https://agentmods.dev/badge/plugins/nvidia/model-optimizer/modelopt.svg" alt="Reviewed on agentmods" width="80" height="20"></a>Grade A, and why
modelopt scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
{
"$schema": "https://json.schemastore.org/claude-code-plugin-manifest.json",
"name": "modelopt",
"displayName": "ModelOpt",
"version": "0.1.0",
"description": "Skills for Model Optimizer development, quantization, deployment, and evaluation.",
"author": {
"name": "NVIDIA Corporation"
},
"homepage": "https://github.com/NVIDIA/Model-Optimizer",
"repository": "https://github.com/NVIDIA/Model-Optimizer",
"license": "Apache-2.0",
"keywords": [
"modelopt",
"quantization",
"evaluation",
"deployment",
"llm"
],
"mcpServers": {
"modelopt": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/NVIDIA/Model-Optimizer.git#subdirectory=tools/mcp",
"modelopt-mcp"
]
}
}
}
What it installs
The manifest is a name and a version. 16 skills travel with it, and installing the plugin installs all of them — 1,564 tokens a session between them. Each is measured on its own page, and each can be installed alone.
- Skill day0-release A 150 tokens
- Skill ptq A 106 tokens
- Skill evaluation A 110 tokens
- Skill benchmark-model-kernels A 105 tokens
- Skill launching-evals A 115 tokens
- Skill monitor A 93 tokens
- Skill release-cherry-pick A 83 tokens
- Skill run-agentx A 38 tokens
- Skill speculative-decoding A 135 tokens
- Skill quant-recipe-search A 148 tokens
- Skill compare-results A 109 tokens
- Skill qad A 69 tokens
- Skill common A 19 tokens
- Skill debug B 87 tokens
- Skill deployment C 117 tokens
- Skill accessing-mlflow C 80 tokens
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 31 lines scan A e848a4668154
modelopt is a plugin published in the GitHub repository NVIDIA/Model-Optimizer (5,398 stars, last pushed today), licensed Apache-2.0. Its token cost is not measured: this kind of file is read by the harness, not the model. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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