RRepoGEO

REPOGEO REPORT · LITE

intel/ipex-llm

Default branch main · commit de6bce27 · scanned 5/11/2026, 6:11:37 AM

GitHub: 8,802 stars · 1,425 forks

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface intel/ipex-llm, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • hightopics#1
    Add specific Intel hardware and LLM acceleration topics

    Why:

    CURRENT
    gpu, llm, pytorch, transformers
    COPY-PASTE FIX
    gpu, llm, pytorch, transformers, intel, npu, igpu, discrete-gpu, llm-acceleration
  • highhomepage#2
    Add a homepage URL to the repository About section

    Why:

    COPY-PASTE FIX
    https://github.com/intel/ipex-llm
  • mediumreadme#3
    Integrate project status into the main README content

    Why:

    CURRENT
    # 💫 Intel® LLM Library for PyTorch*
<p>
  <b>< English</b> | <a href='./README.zh-CN.md'>中文</a> >
</p>

**`IPEX-LLM`** is an LLM acceleration library for Intel [GPU]...
    COPY-PASTE FIX
    # 💫 Intel® LLM Library for PyTorch*

> [!IMPORTANT]
> **THIS PROJECT IS ARCHIVED.** Intel will not provide or guarantee development of or support for this project, including but not limited to, maintenance, bug fixes, new releases or updates. Patches to this project are no longer accepted by Intel. This project has been identified as having known security issues.

<p>
  <b>< English</b> | <a href='./README.zh-CN.md'>中文</a> >
</p>

**`IPEX-LLM`** is an LLM acceleration library for Intel [GPU]...

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface intel/ipex-llm
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenVINO Toolkit
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenVINO Toolkit · recommended 1×
  2. Intel Extension for PyTorch (IPEX) · recommended 1×
  3. ONNX Runtime · recommended 1×
  4. llama.cpp · recommended 1×
  5. Intel oneAPI Base Toolkit · recommended 1×
  • CATEGORY QUERY
    How to accelerate local large language model inference on Intel integrated graphics?
    you: not recommended
    AI recommended (in order):
    1. OpenVINO Toolkit
    2. Intel Extension for PyTorch (IPEX)
    3. ONNX Runtime
    4. llama.cpp
    5. Intel oneAPI Base Toolkit

    AI recommended 5 alternatives but never named intel/ipex-llm. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What libraries optimize finetuning and running LLMs on Intel discrete GPUs and NPUs?
    you: not recommended
    AI recommended (in order):
    1. OpenVINO (openvinotoolkit/openvino)
    2. Intel Extension for PyTorch (IPEX) (intel/intel-extension-for-pytorch)
    3. Intel Extension for TensorFlow (ITEX) (intel/intel-extension-for-tensorflow)
    4. oneAPI Deep Neural Network Library (oneDNN) (oneapi-src/oneDNN)
    5. Hugging Face Accelerate (huggingface/accelerate)
    6. DeepSpeed (microsoft/DeepSpeed)

    AI recommended 6 alternatives but never named intel/ipex-llm. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of intel/ipex-llm?
    pass
    AI named intel/ipex-llm explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts intel/ipex-llm in production, what risks or prerequisites should they evaluate first?
    pass
    AI named intel/ipex-llm explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo intel/ipex-llm solve, and who is the primary audience?
    pass
    AI named intel/ipex-llm explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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intel/ipex-llm — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite