# genpark-llm-inference-throughput-hardware-benchmark-skill

> genpark-llm-inference-throughput-hardware-benchmark-skill — alphaparkinc-genpark-llm-inference-throughput-hardware-benchmark-skill. Use this tool when you need to measure and optimize the performance of large language models (LLMs) on various hardware configurations. It provides real-time inference throughput profiling and benchmarking, helping to identify bottlenecks and improve model efficiency. Ideal for use cases requiring optimized LLM deployment, such as AI model serving, natural language processing, and machine learning applications.

Canonical page: https://skillsregistry.net/skills/alphaparkinc-genpark-llm-inference-throughput-hardware-benchmark-skill  
JSON: https://api.skillsregistry.net/v1/skills/alphaparkinc-genpark-llm-inference-throughput-hardware-benchmark-skill

## Description

Real-time LLM inference throughput profiler & benchmark (Inferock Bench style)

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/alphaparkinc/genpark-llm-inference-throughput-hardware-benchmark-skill)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "alphaparkinc-genpark-llm-inference-throughput-hardware-benchmark-skill"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/alphaparkinc-genpark-llm-inference-throughput-hardware-benchmark-skill` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/alphaparkinc-genpark-llm-inference-throughput-hardware-benchmark-skill/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt