RRepoGEO

REPOGEO REPORT · LITE

ByteDance-Seed/Bagel

Default branch main · commit a2fa77dd · scanned 5/11/2026, 3:52:51 AM

GitHub: 5,901 stars · 523 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 ByteDance-Seed/Bagel, 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
  • highhomepage#1
    Add the homepage URL to the repo's 'About' section

    Why:

    COPY-PASTE FIX
    https://bagel-ai.org/
  • mediumabout#2
    Refine the 'About' description for clarity

    Why:

    CURRENT
    Open-source unified multimodal model
    COPY-PASTE FIX
    Open-source unified multimodal foundation model for understanding and text-to-image generation.

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 ByteDance-Seed/Bagel
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LLaVA
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LLaVA · recommended 1×
  2. InstructBLIP / BLIP-2 · recommended 1×
  3. Stable Diffusion XL (SDXL) · recommended 1×
  4. ControlNet · recommended 1×
  5. IP-Adapter · recommended 1×
  • CATEGORY QUERY
    What open-source models handle both image understanding and text-to-image generation?
    you: not recommended
    AI recommended (in order):
    1. LLaVA
    2. InstructBLIP / BLIP-2
    3. Stable Diffusion XL (SDXL)
    4. ControlNet
    5. IP-Adapter
    6. MiniGPT-4
    7. Kandinsky 2.2

    AI recommended 7 alternatives but never named ByteDance-Seed/Bagel. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a high-performing unified AI model for visual language and image creation tasks.
    you: not recommended
    AI recommended (in order):
    1. GPT-4o
    2. Google Gemini
    3. DALL-E 3
    4. Midjourney
    5. Stable Diffusion XL (stability-ai/generative-models)
    6. Claude 3 Opus

    AI recommended 6 alternatives but never named ByteDance-Seed/Bagel. 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 ByteDance-Seed/Bagel?
    pass
    AI named ByteDance-Seed/Bagel explicitly

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

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

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

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ByteDance-Seed/Bagel — 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