RRepoGEO

REPOGEO REPORT · LITE

FoundationVision/Infinity

Default branch main · commit 9f9fcd1d · scanned 5/28/2026, 9:03:51 PM

GitHub: 1,568 stars · 92 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 FoundationVision/Infinity, 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
  • mediumhomepage#1
    Add the project homepage URL

    Why:

    COPY-PASTE FIX
    https://foundationvision.github.io/infinity.project/
  • lowtopics#2
    Add 'generative-ai' and 'visual-synthesis' topics

    Why:

    CURRENT
    auto-regressive-model, autoregressive-models, generative-model, gpt, gpt-2, image-generation, text-to-image, text-to-image-generation, transformers
    COPY-PASTE FIX
    auto-regressive-model, autoregressive-models, generative-model, gpt, gpt-2, image-generation, text-to-image, text-to-image-generation, transformers, generative-ai, visual-synthesis

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 FoundationVision/Infinity
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
VQGAN
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. VQGAN · recommended 2×
  2. CLIP · recommended 2×
  3. VQ-VAE-2 · recommended 1×
  4. DALL-E · recommended 1×
  5. PixelCNN++ · recommended 1×
  • CATEGORY QUERY
    Need a scalable generative model for high-resolution image synthesis using autoregressive methods.
    you: not recommended
    AI recommended (in order):
    1. VQ-VAE-2
    2. DALL-E
    3. PixelCNN++
    4. ImageGPT
    5. NVAE
    6. VQGAN

    AI recommended 6 alternatives but never named FoundationVision/Infinity. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Exploring advanced generative models for high-fidelity text-to-image generation beyond diffusion.
    you: not recommended
    AI recommended (in order):
    1. StyleGAN
    2. VQGAN
    3. CLIP
    4. NVIDIA GauGAN2
    5. SPADE
    6. BigGAN
    7. CLIP
    8. Pix2PixHD

    AI recommended 8 alternatives but never named FoundationVision/Infinity. 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 FoundationVision/Infinity?
    pass
    AI named FoundationVision/Infinity explicitly

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

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