RRepoGEO

REPOGEO REPORT · LITE

nyu-systems/Grendel-GS

Default branch main · commit 6e50e9a7 · scanned 6/14/2026, 7:18:13 AM

GitHub: 669 stars · 43 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 nyu-systems/Grendel-GS, 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
    Strengthen and reposition the README's opening statement

    Why:

    CURRENT
    The README's first substantive text after the title/subtitle is "We design and implement **Grendel-GS**, which serves as a distributed implementation of 3D Gaussian Splatting training."
    COPY-PASTE FIX
    Grendel-GS is a novel distributed training system for 3D Gaussian Splatting, enabling scalable and high-resolution scene reconstruction. This project, presented at ICLR 2025 Oral, focuses exclusively on accelerating 3D Gaussian Splatting and is under active development.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    3d-gaussian-splatting, gaussian-splatting, distributed-training, deep-learning, computer-vision, neural-rendering, iclr-2025, multi-gpu, scalable-ai
  • mediumcomparison#3
    Add a 'Why Grendel-GS?' or 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    ## Why Grendel-GS?
While general distributed training frameworks like PyTorch Distributed or DeepSpeed provide powerful primitives, Grendel-GS is purpose-built and optimized specifically for the unique challenges of 3D Gaussian Splatting. It offers out-of-the-box solutions for scaling 3DGS training, unlike general frameworks that require significant custom implementation for this domain.

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 nyu-systems/Grendel-GS
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PyTorch Distributed
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. PyTorch Distributed · recommended 2×
  2. DeepSpeed · recommended 2×
  3. PyTorch Lightning · recommended 1×
  4. Hugging Face Accelerate · recommended 1×
  5. Colossal-AI · recommended 1×
  • CATEGORY QUERY
    How to accelerate 3D Gaussian Splatting model training across multiple GPUs?
    you: not recommended
    AI recommended (in order):
    1. PyTorch Distributed
    2. PyTorch Lightning
    3. Hugging Face Accelerate
    4. DeepSpeed
    5. Colossal-AI
    6. JAX

    AI recommended 6 alternatives but never named nyu-systems/Grendel-GS. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a distributed system to efficiently train large-scale 3D Gaussian Splatting models.
    you: not recommended
    AI recommended (in order):
    1. PyTorch Distributed
    2. DeepSpeed
    3. Accelerate
    4. Ray
    5. Horovod

    AI recommended 5 alternatives but never named nyu-systems/Grendel-GS. 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 nyu-systems/Grendel-GS?
    pass
    AI named nyu-systems/Grendel-GS explicitly

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

  • If a team adopts nyu-systems/Grendel-GS in production, what risks or prerequisites should they evaluate first?
    pass
    AI named nyu-systems/Grendel-GS 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 nyu-systems/Grendel-GS solve, and who is the primary audience?
    pass
    AI named nyu-systems/Grendel-GS 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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nyu-systems/Grendel-GS — 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