RRepoGEO

REPOGEO REPORT · LITE

cambrian-mllm/cambrian-s

Default branch main · commit 058b1b4c · scanned 6/1/2026, 11:08:10 AM

GitHub: 548 stars · 19 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 cambrian-mllm/cambrian-s, 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
    Add a concise positioning statement to the README's opening

    Why:

    COPY-PASTE FIX
    Add the following text immediately after the main H1 title: "Cambrian-S is a novel Multimodal Large Language Model (MLLM) designed for advanced spatial supersensing and reasoning in dynamic video streams. It achieves state-of-the-art performance in video analysis through its innovative vision encoder architecture and efficient training strategy."
  • mediumabout#2
    Enhance the repository's 'About' description

    Why:

    CURRENT
    Cambrian-S: Towards Spatial Supersensing in Video
    COPY-PASTE FIX
    Cambrian-S: A robust multimodal LLM for advanced spatial supersensing and reasoning in dynamic video streams, featuring a novel vision encoder and efficient training.
  • lowtopics#3
    Expand topics with more specific keywords for video analysis and spatial reasoning

    Why:

    CURRENT
    computer-vision, llm, multimodal-large-language-models, spatial-understanding, vision-language-model
    COPY-PASTE FIX
    computer-vision, llm, multimodal-large-language-models, spatial-understanding, vision-language-model, video-analysis, video-understanding, spatial-reasoning

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 cambrian-mllm/cambrian-s
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
InternVideo
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. InternVideo · recommended 2×
  2. BLIP-2 · recommended 2×
  3. Perceiver IO · recommended 2×
  4. Video-LLaMA / Video-ChatGPT · recommended 1×
  5. OpenFlamingo · recommended 1×
  • CATEGORY QUERY
    How to improve spatial understanding and reasoning in video analysis using multimodal LLMs?
    you: not recommended
    AI recommended (in order):
    1. Video-LLaMA / Video-ChatGPT
    2. InternVideo
    3. BLIP-2
    4. OpenFlamingo
    5. Perceiver IO
    6. ViT-G/14
    7. MViT

    AI recommended 7 alternatives but never named cambrian-mllm/cambrian-s. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are robust vision-language models for advanced spatial reasoning in dynamic video streams?
    you: not recommended
    AI recommended (in order):
    1. Video-LLaMA
    2. Flamingo
    3. Perceiver IO
    4. InternVideo
    5. CoCa
    6. BLIP-2
    7. Open-Flamingo

    AI recommended 7 alternatives but never named cambrian-mllm/cambrian-s. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • 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 cambrian-mllm/cambrian-s?
    pass
    AI named cambrian-mllm/cambrian-s explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of cambrian-mllm/cambrian-s. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/cambrian-mllm/cambrian-s.svg)](https://repogeo.com/en/r/cambrian-mllm/cambrian-s)
HTML
<a href="https://repogeo.com/en/r/cambrian-mllm/cambrian-s"><img src="https://repogeo.com/badge/cambrian-mllm/cambrian-s.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

cambrian-mllm/cambrian-s — 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