RRepoGEO

REPOGEO REPORT · LITE

nihalsid/mesh-gpt

Default branch main · commit 8de94168 · scanned 6/3/2026, 9:53:06 PM

GitHub: 628 stars · 15 forks

AI VISIBILITY SCORE
18 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
0 pass · 1 warn · 1 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 nihalsid/mesh-gpt, 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
    Rewrite README to introduce MeshGPT and its purpose

    Why:

    CURRENT
    # Code Official code release can be found at: https://github.com/audi/MeshGPT
    COPY-PASTE FIX
    # MeshGPT: Generating Triangle Meshes with Decoder-Only Transformers

This repository contains the code for MeshGPT, a novel deep learning model that directly generates high-quality 3D triangle meshes using a decoder-only transformer architecture. MeshGPT treats meshes as sequences of discrete tokens, enabling direct synthesis of 3D geometry without intermediate representations like point clouds or implicit functions. This project is primarily aimed at researchers and developers in AI, computer graphics, and 3D content creation.

For the official code release and latest updates, please refer to: https://github.com/audi/MeshGPT
  • hightopics#2
    Add relevant topics for discoverability

    Why:

    COPY-PASTE FIX
    3d-modeling, mesh-generation, deep-learning, transformers, computer-graphics, pytorch, generative-ai
  • highlicense#3
    Add a LICENSE file to clarify usage terms

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the root of the repository containing the text of your chosen open-source license (e.g., MIT, Apache-2.0, or GPL-3.0).

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 nihalsid/mesh-gpt
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
facebookresearch/pytorch3d
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. facebookresearch/pytorch3d · recommended 2×
  2. NVIDIA/Kaolin · recommended 2×
  3. tensorflow/graphics · recommended 2×
  4. isl-org/Open3D · recommended 1×
  5. mikedh/trimesh · recommended 1×
  • CATEGORY QUERY
    How can I programmatically generate 3D triangle meshes using deep learning models?
    you: not recommended
    AI recommended (in order):
    1. PyTorch3D (facebookresearch/pytorch3d)
    2. Kaolin (NVIDIA/Kaolin)
    3. Open3D (isl-org/Open3D)
    4. TensorFlow Graphics (tensorflow/graphics)
    5. trimesh (mikedh/trimesh)
    6. vedo (marcomusy/vedo)

    AI recommended 6 alternatives but never named nihalsid/mesh-gpt. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What AI frameworks leverage transformer architectures for synthesizing 3D geometry?
    you: not recommended
    AI recommended (in order):
    1. Open3D-ML (Open3D/Open3D)
    2. PyTorch3D (facebookresearch/pytorch3d)
    3. TensorFlow Graphics (tensorflow/graphics)
    4. Kaolin (NVIDIA/Kaolin)
    5. Perceiver IO (deepmind/deepmind-research)
    6. AlphaFold (deepmind/alphafold)
    7. Hugging Face Transformers (huggingface/transformers)

    AI recommended 7 alternatives but never named nihalsid/mesh-gpt. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    Suggestion:

  • README presence
    warn

    Suggestion:

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 nihalsid/mesh-gpt?
    pass
    AI did not name nihalsid/mesh-gpt — 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 nihalsid/mesh-gpt in production, what risks or prerequisites should they evaluate first?
    pass
    AI named nihalsid/mesh-gpt 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 nihalsid/mesh-gpt solve, and who is the primary audience?
    pass
    AI named nihalsid/mesh-gpt explicitly

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

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite