RRepoGEO

REPOGEO REPORT · LITE

gpu-mode/Triton-Puzzles

Default branch main · commit 4d794abe · scanned 6/27/2026, 5:37:32 AM

GitHub: 2,503 stars · 242 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
28 /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
2 / 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 gpu-mode/Triton-Puzzles, 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
  • hightopics#1
    Add specific topics for Triton, GPU programming, and interactive learning.

    Why:

    CURRENT
    machine-learning, puzzle
    COPY-PASTE FIX
    machine-learning, puzzle, triton, gpu-programming, accelerator, interactive-learning, memory-optimization
  • mediumhomepage#2
    Add a homepage URL to the repository's 'About' section.

    Why:

    COPY-PASTE FIX
    https://colab.research.google.com/github/srush/Triton-Puzzles/blob/main/Triton-Puzzles.ipynb

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 gpu-mode/Triton-Puzzles
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
NVIDIA DLI (Deep Learning Institute)
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. NVIDIA DLI (Deep Learning Institute) · recommended 1×
  2. CodeChef · recommended 1×
  3. LeetCode · recommended 1×
  4. HPC-AI Advisory Council (HPC-AI AC) · recommended 1×
  5. OpenMP · recommended 1×
  • CATEGORY QUERY
    How can I learn GPU accelerator programming concepts through interactive puzzles?
    you: not recommended
    AI recommended (in order):
    1. NVIDIA DLI (Deep Learning Institute)
    2. CodeChef
    3. LeetCode
    4. HPC-AI Advisory Council (HPC-AI AC)
    5. OpenMP
    6. OpenACC
    7. CUDA by Example
    8. Intel oneAPI
    9. DPC++

    AI recommended 9 alternatives but never named gpu-mode/Triton-Puzzles. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking interactive tutorials to master memory optimization for AI accelerator programming.
    you: not recommended
    AI recommended (in order):
    1. NVIDIA DLI (Deep Learning Institute) Courses
    2. Intel oneAPI Training and Workshops
    3. TensorFlow Lite Micro (TFLM) Examples and Tutorials
    4. PyTorch Tutorials
    5. torch.compile
    6. torch.quantization
    7. AMD ROCm Documentation and Examples
    8. OpenVINO Toolkit Tutorials
    9. Google Colaboratory (Colab) Notebooks

    AI recommended 9 alternatives but never named gpu-mode/Triton-Puzzles. 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 gpu-mode/Triton-Puzzles?
    pass
    AI did not name gpu-mode/Triton-Puzzles — likely talking about a different project

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

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

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

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gpu-mode/Triton-Puzzles — 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