RRepoGEO

REPOGEO REPORT · LITE

flagos-ai/FlagGems

Default branch master · commit 2b62cf1d · scanned 6/26/2026, 5:56:56 PM

GitHub: 1,034 stars · 424 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)

3 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 flagos-ai/FlagGems, 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
    Reposition README's opening to explicitly state core purpose

    Why:

    CURRENT
    The README currently starts with links and social media icons before the 'About' section.
    COPY-PASTE FIX
    FlagGems is a high-performance, hardware-agnostic operator library implemented in Triton language, designed to accelerate Large Language Model (LLM) training and inference across diverse AI accelerators.

[](https://flagos.io/)

[中文版](./README_cn.md) | English

<div align="right">
  <a href="https://www.linkedin.com/company/flagos-community" target="_blank">
    
  </a>
  • mediumtopics#2
    Expand topics to include broader LLM acceleration and hardware-agnostic terms

    Why:

    CURRENT
    pytorch, triton, triton-kernels
    COPY-PASTE FIX
    pytorch, triton, triton-kernels, llm-acceleration, hardware-agnostic, ai-accelerators, deep-learning-inference, deep-learning-training
  • lowhomepage#3
    Add the project homepage URL

    Why:

    COPY-PASTE FIX
    https://flagos.io/

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 flagos-ai/FlagGems
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PyTorch
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. PyTorch · recommended 2×
  2. DeepSpeed · recommended 2×
  3. Hugging Face Optimum · recommended 1×
  4. OpenAI Triton · recommended 1×
  5. TensorRT-LLM · recommended 1×
  • CATEGORY QUERY
    How to accelerate large language model operations using Triton kernels for better performance?
    you: not recommended
    AI recommended (in order):
    1. PyTorch
    2. Hugging Face Optimum
    3. OpenAI Triton
    4. TensorRT-LLM
    5. DeepSpeed
    6. jax-triton

    AI recommended 6 alternatives but never named flagos-ai/FlagGems. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a hardware-agnostic operator library for efficient LLM inference and training across various AI accelerators.
    you: not recommended
    AI recommended (in order):
    1. OpenVINO
    2. ONNX Runtime
    3. Apache TVM
    4. TensorRT
    5. XLA
    6. DeepSpeed
    7. PyTorch
    8. TensorFlow

    AI recommended 8 alternatives but never named flagos-ai/FlagGems. 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 flagos-ai/FlagGems?
    pass
    AI named flagos-ai/FlagGems explicitly

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

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

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

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MARKDOWN (README)
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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite