RRepoGEO

REPOGEO REPORT · LITE

deepseek-ai/DeepGEMM

Default branch main · commit 54e22612 · scanned 6/28/2026, 1:56:49 AM

GitHub: 7,437 stars · 1,071 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 deepseek-ai/DeepGEMM, 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
    Rephrase 'learning resource' to emphasize production efficiency

    Why:

    CURRENT
    The library is designed for simplicity, with only a limited number of core kernel functions, making it a clean and accessible resource for learning NVIDIA GPU kernel optimization techniques.
    COPY-PASTE FIX
    The library is designed for simplicity and efficiency, offering a streamlined set of core kernel functions that simplify development and integration of advanced NVIDIA GPU kernel optimizations for production use.
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/deepseek-ai/DeepGEMM

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 deepseek-ai/DeepGEMM
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
NVIDIA cuBLAS / cuBLASLt
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. NVIDIA cuBLAS / cuBLASLt · recommended 1×
  2. AMD rocBLAS · recommended 1×
  3. Intel oneMKL · recommended 1×
  4. FlashAttention / FlashAttention-2 · recommended 1×
  5. NVIDIA CUTLASS · recommended 1×
  • CATEGORY QUERY
    How to optimize GPU matrix multiplication for large language models efficiently?
    you: not recommended
    AI recommended (in order):
    1. NVIDIA cuBLAS / cuBLASLt
    2. AMD rocBLAS
    3. Intel oneMKL
    4. FlashAttention / FlashAttention-2
    5. NVIDIA CUTLASS
    6. TVM / Apache TVM
    7. OpenBLAS / BLIS

    AI recommended 7 alternatives but never named deepseek-ai/DeepGEMM. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a high-performance CUDA library for mixed-precision tensor operations with JIT compilation.
    you: not recommended
    AI recommended (in order):
    1. PyTorch
    2. TensorFlow
    3. XLA
    4. JAX
    5. Apache TVM
    6. cuBLAS
    7. cuDNN
    8. CUTLASS

    AI recommended 8 alternatives but never named deepseek-ai/DeepGEMM. 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 deepseek-ai/DeepGEMM?
    pass
    AI named deepseek-ai/DeepGEMM explicitly

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

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

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

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deepseek-ai/DeepGEMM — 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