RRepoGEO

REPOGEO REPORT · LITE

NVlabs/Sana

Default branch main · commit 1bfb9352 · scanned 5/13/2026, 9:07:19 PM

GitHub: 5,134 stars · 346 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 NVlabs/Sana, 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
    Clarify the README's opening sentence to state Sana's core purpose

    Why:

    CURRENT
    SANA is an efficiency-oriented codebase f
    COPY-PASTE FIX
    SANA is an efficiency-oriented codebase for **high-resolution image and video synthesis** using **Linear Diffusion Transformers**. It enables efficient generation of high-quality visual content.
  • mediumtopics#2
    Expand repository topics to include more specific generative AI terms

    Why:

    CURRENT
    diffusion, dit, linear-transformer, nvfp4, pytorch, reinforcement-learning, sana, system-algorithm-deisgn, text-to-image-generation, text-to-video, transformers, video-generation
    COPY-PASTE FIX
    diffusion, dit, linear-transformer, nvfp4, pytorch, reinforcement-learning, sana, system-algorithm-deisgn, text-to-image-generation, text-to-video, transformers, video-generation, high-resolution-synthesis, efficient-generation, generative-ai, image-synthesis, video-synthesis
  • lowreadme#3
    Add a prominent "Quick Start" section to the README

    Why:

    COPY-PASTE FIX
    ## ✨ Quick Start

To get started with SANA, explore our [official documentation](https://nvlabs.github.io/Sana/docs/) for installation and usage guides. You can also try our [live demo](https://nv-sana.mit.edu/) or find models on [HuggingFace](https://huggingface.co/collections/Efficient-Large-Model/sana).

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 NVlabs/Sana
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Stable Diffusion XL (SDXL)
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Stable Diffusion XL (SDXL) · recommended 1×
  2. ComfyUI · recommended 1×
  3. 4x-UltraSharp · recommended 1×
  4. ESRGAN · recommended 1×
  5. ControlNet · recommended 1×
  • CATEGORY QUERY
    How can I efficiently create high-resolution images and videos with diffusion models?
    you: not recommended
    AI recommended (in order):
    1. Stable Diffusion XL (SDXL)
    2. ComfyUI
    3. 4x-UltraSharp
    4. ESRGAN
    5. ControlNet
    6. Automatic1111 Stable Diffusion WebUI
    7. High-Res Fix
    8. Latent (nearest, bicubic)
    9. SwinIR
    10. Tiled Diffusion / MultiDiffusion extensions
    11. RunwayML Gen-2
    12. Pika Labs
    13. AnimateDiff
    14. Stable Video Diffusion (SVD)
    15. Fooocus

    AI recommended 15 alternatives but never named NVlabs/Sana. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a PyTorch library for efficient text-to-video generation using transformer architectures.
    you: not recommended
    AI recommended (in order):
    1. VideoCrafter

    AI recommended 1 alternative but never named NVlabs/Sana. 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 NVlabs/Sana?
    pass
    AI named NVlabs/Sana explicitly

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

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

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

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MARKDOWN (README)
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NVlabs/Sana — 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