RRepoGEO

REPOGEO REPORT · LITE

rhymes-ai/Aria

Default branch main · commit 9b25fecb · scanned 5/10/2026, 2:08:21 AM

GitHub: 1,087 stars · 88 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 rhymes-ai/Aria, 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
  • highreadme#1
    Reposition README introduction to clarify Aria's core identity

    Why:

    CURRENT
    Aria is a multimodal native MoE model. It features:
    COPY-PASTE FIX
    Aria is a state-of-the-art open-source multimodal Mixture-of-Experts (MoE) model. It excels in advanced vision-language tasks, particularly video and document understanding, and is designed for efficient large-scale applications.
  • highhomepage#2
    Add a project homepage URL to repository metadata

    Why:

    COPY-PASTE FIX
    Add the official project homepage URL (e.g., a dedicated project page, documentation site, or main company page for Aria) to the repository's 'About' section.
  • mediumreadme#3
    Add a 'Target Use Cases' or 'Who is Aria for?' section

    Why:

    COPY-PASTE FIX
    Add a new section, perhaps after 'Introduction' or 'Features', titled 'Target Use Cases' or 'Who is Aria for?', with content like: 'Aria is ideal for researchers and developers building applications that require: - State-of-the-art multimodal understanding, especially for video and complex documents. - Long context window processing for vision-language tasks. - Efficient inference and fine-tuning of large MoE models.'

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 rhymes-ai/Aria
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Video-LLaMA
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Video-LLaMA · recommended 1×
  2. LLaVA · recommended 1×
  3. BLIP-2 · recommended 1×
  4. OpenFlamingo · recommended 1×
  5. MiniGPT-4 · recommended 1×
  • CATEGORY QUERY
    What open-source multimodal mixture-of-experts models excel at video and document understanding?
    you: not recommended
    AI recommended (in order):
    1. Video-LLaMA
    2. LLaVA
    3. BLIP-2
    4. OpenFlamingo
    5. MiniGPT-4

    AI recommended 5 alternatives but never named rhymes-ai/Aria. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a performant multimodal model with long context for efficient large-scale vision-language tasks.
    you: not recommended
    AI recommended (in order):
    1. GPT-4o
    2. Gemini 1.5 Pro
    3. Claude 3 Opus
    4. LLaVA-1.6 (haotian-liu/LLaVA)
    5. Fuyu-8B (AdeptAILabs/fuyu-8b)

    AI recommended 5 alternatives but never named rhymes-ai/Aria. 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 rhymes-ai/Aria?
    pass
    AI named rhymes-ai/Aria explicitly

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

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

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

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rhymes-ai/Aria — 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