RRepoGEO

REPOGEO REPORT · LITE

Dao-AILab/sonic-moe

Default branch main · commit cfbd65f3 · scanned 6/8/2026, 10:06:56 PM

GitHub: 707 stars · 88 forks

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 Dao-AILab/sonic-moe, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    mixture-of-experts, moe, gpu-optimization, deep-learning-acceleration, nvidia-hopper, nvidia-blackwell, triton, cutlass, ai-acceleration
  • highreadme#2
    Clarify SonicMoE's role as a specialized MoE acceleration library in the README's opening

    Why:

    CURRENT
    # SonicMoE: Accelerating MoE with IO and Tile-aware Optimizations
    COPY-PASTE FIX
    # SonicMoE: A Specialized Library for Blazing-Fast Mixture-of-Experts (MoE) Acceleration on NVIDIA Hopper and Blackwell GPUs
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://arxiv.org/abs/2512.14080

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 Dao-AILab/sonic-moe
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
DeepSpeed
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. DeepSpeed · recommended 1×
  2. Megatron-LM · recommended 1×
  3. FairScale · recommended 1×
  4. PyTorch FSDP · recommended 1×
  5. Accelerate · recommended 1×
  • CATEGORY QUERY
    How to optimize Mixture-of-Experts model training for latest GPU architectures?
    you: not recommended
    AI recommended (in order):
    1. DeepSpeed
    2. Megatron-LM
    3. FairScale
    4. PyTorch FSDP
    5. Accelerate
    6. Colossal-AI

    AI recommended 6 alternatives but never named Dao-AILab/sonic-moe. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools provide IO-aware optimizations for accelerating MoE model performance?
    you: not recommended
    AI recommended (in order):
    1. DeepSpeed (microsoft/DeepSpeed)
    2. FairScale (facebookresearch/fairscale)
    3. PyTorch FSDP (pytorch/pytorch)
    4. Megatron-LM (NVIDIA/Megatron-LM)
    5. Ray (ray-project/ray)
    6. Accelerate (huggingface/accelerate)
    7. NVIDIA DALI (NVIDIA/DALI)

    AI recommended 7 alternatives but never named Dao-AILab/sonic-moe. 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 Dao-AILab/sonic-moe?
    pass
    AI named Dao-AILab/sonic-moe explicitly

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

  • If a team adopts Dao-AILab/sonic-moe in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Dao-AILab/sonic-moe 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 Dao-AILab/sonic-moe solve, and who is the primary audience?
    pass
    AI named Dao-AILab/sonic-moe 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 Dao-AILab/sonic-moe. 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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Dao-AILab/sonic-moe — 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