# Torch Xpu Profile

> Profile a Hugging Face model on Intel GPU at the PyTorch level with torch.profiler and Kineto. Captures CPU + XPU timeline, exports Chrome trace, identifies hottest kernels and async-overlap gaps. Use when the user asks why a model is slow, which op is the bottleneck, or where the GPU is idle. Not for profiling inside a running vLLM server (use vllm-xpu-profile) or for SYCL-kernel-level signal beneath the PyTorch op layer (use xpu-profile-unitrace).

## Facts
- Page: https://tashan.sh/capability/plugin-intel-gpu-ai-skills-torch-xpu-profile
- tashan id: plugin:intel/gpu-ai-skills/torch-xpu-profile
- Source: https://github.com/intel/gpu-ai-skills
- Type: plugin
- Category: other
- tashan score: 45.0 / 100
- Adoption: 7.0
- Upkeep: 100.0
- Freshness: 99.0
- Evidence coverage: 84% of the inputs this score can use
- Health: active
- Instruction depth: not yet graded
- License: Apache-2.0
- Official: no

## Install

```sh
/plugin marketplace add intel/gpu-ai-skills
/plugin install torch-xpu-profile@intel-model-skillpack
```

## Security audit
Not scanned. We audit npm-published capabilities; this one has no npm package we can resolve, or has not reached the queue. This is not a clean bill of health.

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Measured 2026-09-13 by tashan (https://tashan.sh) from public evidence. Scorer s5.