RRepoGEO

REPOGEO REPORT · LITE

ByteDance-Seed/seed-oss

Default branch master · commit 98e12be7 · scanned 6/15/2026, 12:07:52 PM

GitHub: 885 stars · 50 forks

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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/seed-oss, 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 repository description

    Why:

    COPY-PASTE FIX
    A series of open-source large language models (LLMs) from ByteDance's Seed Team, designed for powerful long-context, reasoning, and agent capabilities, optimized for international use cases.
  • mediumhomepage#2
    Add the official project homepage link

    Why:

    COPY-PASTE FIX
    https://seed.bytedance.com/

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/seed-oss
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Llama 3
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Llama 3 · recommended 2×
  2. Mixtral 8x7B Instruct · recommended 1×
  3. Qwen2 · recommended 1×
  4. Gemma 2 · recommended 1×
  5. CodeLlama · recommended 1×
  • CATEGORY QUERY
    What are some open-source large language models with strong reasoning and agent capabilities?
    you: not recommended
    AI recommended (in order):
    1. Llama 3
    2. Mixtral 8x7B Instruct
    3. Qwen2
    4. Gemma 2
    5. CodeLlama
    6. Falcon 180B Instruct

    AI recommended 6 alternatives but never named ByteDance-Seed/seed-oss. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking developer-friendly open-source LLMs offering excellent performance on common benchmarks.
    you: not recommended
    AI recommended (in order):
    1. Llama 3
    2. Mixtral
    3. Gemma
    4. Mistral 7B
    5. Qwen
    6. Falcon
    7. Phi-3

    AI recommended 7 alternatives but never named ByteDance-Seed/seed-oss. 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 ByteDance-Seed/seed-oss?
    pass
    AI named ByteDance-Seed/seed-oss 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/seed-oss in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ByteDance-Seed/seed-oss 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/seed-oss solve, and who is the primary audience?
    pass
    AI named ByteDance-Seed/seed-oss 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/seed-oss — 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