RRepoGEO

REPOGEO REPORT · LITE

google-research/parti

Default branch main · commit 5a657978 · scanned 6/20/2026, 9:43:06 PM

GitHub: 1,592 stars · 84 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
45 /100
Critical
Category recall
1 / 2
Avg rank #5.0 when recommended
Rule findings
1 pass · 0 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 google-research/parti, 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
  • highabout#1
    Add a concise description to the About section

    Why:

    COPY-PASTE FIX
    Parti is an autoregressive text-to-image model from Google Research, uniquely treating image generation as a sequence-to-sequence modeling problem to achieve high-fidelity photorealistic synthesis.
  • mediumhomepage#2
    Add a homepage URL to the About section

    Why:

    COPY-PASTE FIX
    https://parti.research.google

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
1 / 2
50% of queries surface google-research/parti
Avg rank
#5.0
Lower is better. #1 = top recommendation.
Share of voice
7%
Of all named tools, what % are you?
Top rival
DALL-E 3
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. DALL-E 3 · recommended 1×
  2. ChatGPT Plus · recommended 1×
  3. Microsoft Copilot · recommended 1×
  4. Designer · recommended 1×
  5. Imagen · recommended 1×
  • CATEGORY QUERY
    What are the best autoregressive models for generating detailed images from text prompts?
    you: #5
    AI recommended (in order):
    1. DALL-E 3
    2. ChatGPT Plus
    3. Microsoft Copilot
    4. Designer
    5. Parti ← you
    6. Imagen
    7. VQ-GAN + Transformer
    8. VQGAN-CLIP
    9. DALL-E 2
    Show full AI answer
  • CATEGORY QUERY
    Which text-to-image generation systems use a sequence-to-sequence modeling approach?
    you: not recommended
    AI recommended (in order):
    1. AttnGAN
    2. StackGAN
    3. VQ-VAE-2
    4. DALL-E (original)
    5. Image Transformer

    AI recommended 5 alternatives but never named google-research/parti. 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
    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 google-research/parti?
    pass
    AI named google-research/parti explicitly

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

  • If a team adopts google-research/parti in production, what risks or prerequisites should they evaluate first?
    pass
    AI named google-research/parti 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 google-research/parti solve, and who is the primary audience?
    pass
    AI did not name google-research/parti — 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?

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MARKDOWN (README)
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google-research/parti — 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