RRepoGEO

REPOGEO REPORT · LITE

nvidia-cosmos/cosmos-transfer1

Default branch main · commit 5005e823 · scanned 6/14/2026, 4:22:09 PM

GitHub: 807 stars · 104 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 nvidia-cosmos/cosmos-transfer1, 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 improve categorization

    Why:

    COPY-PASTE FIX
    physical-ai, world-model, transfer-learning, simulation, multimodal, foundation-model, deprecated, cosmos-transfer1
  • highabout#2
    Update the repository description to reflect its deprecated status

    Why:

    CURRENT
    Cosmos-Transfer1 is a world-to-world transfer model designed to bridge the perceptual divide between simulated and real-world environments.
    COPY-PASTE FIX
    Cosmos-Transfer1 is a deprecated world-to-world transfer model for Physical AI, bridging simulated and real-world environments. Please migrate to Cosmos 3 (github.com/NVIDIA/Cosmos) for the latest capabilities.
  • mediumreadme#3
    Enhance the initial descriptive sentence in the README

    Why:

    CURRENT
    Cosmos-Transfer1 is a key branch of Cosmos World Foundation Models (WFMs) specialized for multimodal controllable conditional world generation or world2world transfer.
    COPY-PASTE FIX
    Cosmos-Transfer1 is a **foundation model** for **Physical AI**, specifically a key branch of Cosmos World Foundation Models (WFMs) specialized for multimodal controllable conditional world generation or world2world transfer, bridging the perceptual divide between simulated and real-world environments.

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 nvidia-cosmos/cosmos-transfer1
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
NVIDIA Isaac Sim
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. NVIDIA Isaac Sim · recommended 1×
  2. ROS/ROS 2 · recommended 1×
  3. Unity 3D · recommended 1×
  4. Unity ML-Agents Toolkit · recommended 1×
  5. Unreal Engine · recommended 1×
  • CATEGORY QUERY
    How to bridge the perceptual gap between simulated and real-world AI environments?
    you: not recommended
    AI recommended (in order):
    1. NVIDIA Isaac Sim
    2. ROS/ROS 2
    3. Unity 3D
    4. Unity ML-Agents Toolkit
    5. Unreal Engine
    6. AirSim
    7. Gazebo
    8. MuJoCo
    9. PyBullet
    10. DeepMind Lab
    11. DMControl

    AI recommended 11 alternatives but never named nvidia-cosmos/cosmos-transfer1. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking tools for transforming and adapting AI models across diverse sensor domains and embodiments.
    you: not recommended
    AI recommended (in order):
    1. OpenVINO
    2. ONNX Runtime
    3. TensorFlow Lite
    4. TensorFlow Extended (TFX)
    5. PyTorch Mobile
    6. TorchScript
    7. NVIDIA TensorRT
    8. Edge Impulse
    9. MLflow

    AI recommended 9 alternatives but never named nvidia-cosmos/cosmos-transfer1. 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 nvidia-cosmos/cosmos-transfer1?
    pass
    AI named nvidia-cosmos/cosmos-transfer1 explicitly

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

  • If a team adopts nvidia-cosmos/cosmos-transfer1 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named nvidia-cosmos/cosmos-transfer1 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 nvidia-cosmos/cosmos-transfer1 solve, and who is the primary audience?
    pass
    AI named nvidia-cosmos/cosmos-transfer1 explicitly

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

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nvidia-cosmos/cosmos-transfer1 — 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