RRepoGEO

REPOGEO REPORT · LITE

pytorch/executorch

Default branch main · commit 12c1195e · scanned 5/14/2026, 1:32:07 PM

GitHub: 4,605 stars · 997 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 pytorch/executorch, 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
  • highreadme#1
    Add a direct comparison paragraph to the 'Why ExecuTorch?' section

    Why:

    COPY-PASTE FIX
    Add a paragraph to the 'Why ExecuTorch?' section that explicitly positions ExecuTorch against its competitors. For example: 'While alternatives like TensorFlow Lite, PyTorch Mobile, and ONNX Runtime address on-device deployment, ExecuTorch stands out as PyTorch's unified, highly optimized, and lightweight native runtime. It is specifically engineered for resource-constrained edge and mobile devices, streamlining deployment by eliminating manual C++ rewrites and complex format conversions often required by other frameworks.'
  • mediumtopics#2
    Add more specific topics related to on-device inference and runtime

    Why:

    CURRENT
    deep-learning, embedded, gpu, machine-learning, mobile, neural-network, tensor
    COPY-PASTE FIX
    deep-learning, embedded, gpu, machine-learning, mobile, neural-network, tensor, on-device-inference, edge-ai, ai-runtime, model-deployment, pytorch-inference
  • lowlicense#3
    Clarify the project's license in the README

    Why:

    COPY-PASTE FIX
    Add a line to the README, for example in the 'Getting Started' or 'Contributing' section, stating: 'ExecuTorch is licensed under [Insert specific license name(s) here, e.g., a custom license combining Apache 2.0 and MIT]. Please refer to the `LICENSE` file for complete details.'

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 pytorch/executorch
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
TensorFlow Lite
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. TensorFlow Lite · recommended 2×
  2. PyTorch Mobile · recommended 2×
  3. ONNX Runtime · recommended 2×
  4. OpenVINO Toolkit · recommended 2×
  5. Core ML · recommended 1×
  • CATEGORY QUERY
    How to deploy deep learning models efficiently on resource-constrained mobile and edge devices?
    you: not recommended
    AI recommended (in order):
    1. TensorFlow Lite
    2. PyTorch Mobile
    3. ONNX Runtime
    4. Core ML
    5. MediaPipe
    6. OpenVINO Toolkit
    7. TVM (Apache TVM)

    AI recommended 7 alternatives but never named pytorch/executorch. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help optimize and deploy existing neural network models to embedded systems without C++?
    you: not recommended
    AI recommended (in order):
    1. TensorFlow Lite
    2. PyTorch Mobile
    3. ONNX Runtime
    4. OpenVINO Toolkit
    5. Edge Impulse
    6. Apache TVM

    AI recommended 6 alternatives but never named pytorch/executorch. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 pytorch/executorch?
    pass
    AI named pytorch/executorch explicitly

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

  • If a team adopts pytorch/executorch in production, what risks or prerequisites should they evaluate first?
    pass
    AI named pytorch/executorch 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 pytorch/executorch solve, and who is the primary audience?
    pass
    AI named pytorch/executorch explicitly

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

Embed your GEO score

Drop this badge into the README of pytorch/executorch. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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pytorch/executorch — 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