RRepoGEO

REPOGEO REPORT · LITE

google-ai-edge/LiteRT

Default branch main · commit 21ad8477 · scanned 6/18/2026, 3:56:13 AM

GitHub: 2,568 stars · 344 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 google-ai-edge/LiteRT, 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

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

OVERALL DIRECTION
  • mediumreadme#1
    Strengthen README's opening to explicitly position LiteRT against competitors

    Why:

    CURRENT
    Google's on-device runtime for high-performance ML & GenAI deployment on edge platforms.
    COPY-PASTE FIX
    LiteRT is Google's next-generation on-device runtime, succeeding TensorFlow Lite, for high-performance ML & GenAI deployment on edge platforms. It offers a powerful alternative to solutions like NVIDIA TensorRT, OpenVINO, and ONNX Runtime for efficient model conversion, runtime, and optimization.
  • lowreadme#2
    Add a comparison section to the README

    Why:

    COPY-PASTE FIX
    Consider adding a new section, e.g., "## 🆚 LiteRT vs. Alternatives", to explicitly compare LiteRT's strengths (e.g., GenAI focus, WebGPU/WASM, Google backing, edge optimization) against common competitors like NVIDIA TensorRT, OpenVINO Toolkit, and ONNX Runtime.

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 google-ai-edge/LiteRT
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
NVIDIA TensorRT
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. NVIDIA TensorRT · recommended 2×
  2. OpenVINO Toolkit · recommended 2×
  3. ONNX Runtime · recommended 2×
  4. Core ML · recommended 2×
  5. TFLite (TensorFlow Lite) · recommended 1×
  • CATEGORY QUERY
    Seeking an on-device runtime for accelerating ML and generative AI models on edge hardware.
    you: not recommended
    AI recommended (in order):
    1. NVIDIA TensorRT
    2. OpenVINO Toolkit
    3. ONNX Runtime
    4. TFLite (TensorFlow Lite)
    5. PyTorch Mobile / LibTorch
    6. Core ML
    7. TVM (Apache TVM)

    AI recommended 7 alternatives but never named google-ai-edge/LiteRT. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tools for optimizing and converting large AI models for efficient on-device execution?
    you: not recommended
    AI recommended (in order):
    1. OpenVINO Toolkit
    2. TensorFlow Lite
    3. ONNX Runtime
    4. PyTorch Mobile
    5. NVIDIA TensorRT
    6. Core ML
    7. Apache TVM

    AI recommended 7 alternatives but never named google-ai-edge/LiteRT. 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 google-ai-edge/LiteRT?
    pass
    AI named google-ai-edge/LiteRT explicitly

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

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

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

Embed your GEO score

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MARKDOWN (README)
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HTML
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google-ai-edge/LiteRT — 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