RRepoGEO

REPOGEO REPORT · LITE

NVlabs/Sana

Default branch main · commit 59629fdf · scanned 6/24/2026, 8:02:47 AM

GitHub: 8,356 stars · 664 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)

3 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 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
    Add a clear, concise opening statement to the README

    Why:

    CURRENT
    The README excerpt starts with a series of links and badges, pushing the core description down.
    COPY-PASTE FIX
    SANA is an efficient framework for high-resolution image and video synthesis, leveraging linear diffusion transformers to accelerate generation and improve quality.
  • mediumtopics#2
    Add specific topics to reinforce core functionality

    Why:

    CURRENT
    diffusion, dit, linear-transformer, nvfp4, pytorch, reinforcement-learning, sana, streaming-video, system-algorithm-deisgn, text-to-image-generation, text-to-video, transformers, video-generation, world-models
    COPY-PASTE FIX
    diffusion, dit, high-resolution, image-synthesis, linear-transformer, nvfp4, pytorch, reinforcement-learning, sana, streaming-video, system-algorithm-deisgn, text-to-image-generation, text-to-video, transformers, video-generation, world-models
  • lowreadme#3
    Add a concise 'Key Features' section to the README

    Why:

    COPY-PASTE FIX
    ### Key Features
- **Efficient High-Resolution Synthesis:** Generate detailed images and videos rapidly.
- **Linear Diffusion Transformers:** Leverage advanced architectures for scalable performance.
- **Unified Framework:** Supports various SANA models including SANA-1.5, SANA-Sprint, and SANA-Video.

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. DeepFloyd IF · recommended 1×
  3. Midjourney · recommended 1×
  4. RunwayML Gen-2 · recommended 1×
  5. Pika Labs · recommended 1×
  • CATEGORY QUERY
    How to efficiently generate high-resolution images and videos using diffusion transformers?
    you: not recommended
    AI recommended (in order):
    1. Stable Diffusion XL (SDXL)
    2. DeepFloyd IF
    3. Midjourney
    4. RunwayML Gen-2
    5. Pika Labs
    6. ComfyUI
    7. AnimateDiff

    AI recommended 7 alternatives but never named NVlabs/Sana. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a PyTorch library for text-to-video generation using linear transformer architectures.
    you: not recommended
    AI recommended (in order):
    1. VideoGPT
    2. Make-A-Video
    3. Phenaki
    4. Open-sora/sora-pytorch
    5. Long-Short Transformer (LST)
    6. Performer
    7. Reformer
    8. Hugging Face Transformers

    AI recommended 8 alternatives 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?

Embed your GEO score

Drop this badge into the README of NVlabs/Sana. 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/NVlabs/Sana.svg)](https://repogeo.com/en/r/NVlabs/Sana)
HTML
<a href="https://repogeo.com/en/r/NVlabs/Sana"><img src="https://repogeo.com/badge/NVlabs/Sana.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

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