RRepoGEO

REPOGEO REPORT · LITE

SandAI-org/MAGI-1

Default branch main · commit 0fcefdef · scanned 6/18/2026, 6:23:00 PM

GitHub: 3,708 stars · 238 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
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 SandAI-org/MAGI-1, 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
    Strengthen the README's 'About' section opening to explicitly state MAGI-1's core purpose and audience

    Why:

    CURRENT
    We present MAGI-1, a world model that generates videos by autoregressivelypredicting a sequence of video chunks, defined as fixed-length
    COPY-PASTE FIX
    We present MAGI-1, an open-source world model for autoregressive video generation at scale, designed for researchers and developers. It generates high-quality videos by autoregressively predicting a sequence of video chunks, defined as fixed-length...
  • highabout#2
    Add 'open-source' to the repository description

    Why:

    CURRENT
    MAGI-1: Autoregressive Video Generation at Scale
    COPY-PASTE FIX
    MAGI-1: Open-source Autoregressive Video Generation at Scale
  • mediumreadme#3
    Add a dedicated section or prominent mention of ComfyUI support in the README's main body

    Why:

    COPY-PASTE FIX
    ## Key Features
- **Autoregressive Video Generation:** Generates high-quality videos by predicting sequences of video chunks.
- **Scalable World Model:** Designed for large-scale applications and research.
- **ComfyUI Integration:** Seamlessly integrate MAGI-1 into your ComfyUI workflows with custom nodes available.

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 SandAI-org/MAGI-1
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Phenaki / WALT
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Phenaki / WALT · recommended 1×
  2. Make-A-Video · recommended 1×
  3. RunwayML · recommended 1×
  4. Pika Labs · recommended 1×
  5. Stable Diffusion · recommended 1×
  • CATEGORY QUERY
    How can I generate high-quality videos using autoregressive AI models at scale?
    you: not recommended
    AI recommended (in order):
    1. Phenaki / WALT
    2. Make-A-Video
    3. RunwayML
    4. Pika Labs
    5. Stable Diffusion
    6. Sora

    AI recommended 6 alternatives but never named SandAI-org/MAGI-1. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Which open-source projects offer autoregressive video generation, especially with ComfyUI support?
    you: not recommended
    AI recommended (in order):
    1. Stable Video Diffusion (SVD) (stabilityai/stable-video-diffusion-img2vid-xt)
    2. ComfyUI-SVD
    3. AnimateDiff
    4. ComfyUI-AnimateDiff-Evolved
    5. VideoCrafter
    6. ModelScope Text-to-Video Synthesis
    7. CogVideo

    AI recommended 7 alternatives but never named SandAI-org/MAGI-1. 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 SandAI-org/MAGI-1?
    pass
    AI named SandAI-org/MAGI-1 explicitly

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

  • If a team adopts SandAI-org/MAGI-1 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named SandAI-org/MAGI-1 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 SandAI-org/MAGI-1 solve, and who is the primary audience?
    pass
    AI named SandAI-org/MAGI-1 explicitly

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

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SandAI-org/MAGI-1 — 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