RRepoGEO

REPOGEO REPORT · LITE

openai/consistencydecoder

Default branch main · commit 22a04490 · scanned 5/23/2026, 6:57:58 PM

GitHub: 2,214 stars · 80 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
28 /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
2 / 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 openai/consistencydecoder, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition the README's opening sentence to clarify its role as a solution

    Why:

    CURRENT
    Improved decoding for stable diffusion vaes.
    COPY-PASTE FIX
    Consistency Decoder provides an improved, faster, and higher-quality decoding method for latent representations from diffusion model VAEs, such as those found in Stable Diffusion. It enables efficient, high-fidelity image generation with significantly fewer inference steps by leveraging consistency models.
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://arxiv.org/abs/2303.01469

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 openai/consistencydecoder
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Stable Diffusion's VAE
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Stable Diffusion's VAE · recommended 1×
  2. VQGAN · recommended 1×
  3. LAION-5B · recommended 1×
  4. ImageNet · recommended 1×
  5. OpenImages · recommended 1×
  • CATEGORY QUERY
    How to improve image quality when decoding latent representations from diffusion model VAEs?
    you: not recommended
    AI recommended (in order):
    1. Stable Diffusion's VAE
    2. VQGAN
    3. LAION-5B
    4. ImageNet
    5. OpenImages
    6. LPIPS
    7. torchmetrics
    8. lpips library
    9. ESRGAN
    10. Real-ESRGAN
    11. SwinIR
    12. Latent Diffusion Models
    13. Stable Diffusion
    14. torch.cuda.amp

    AI recommended 14 alternatives but never named openai/consistencydecoder. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for better decoding methods for VAE latent spaces in generative AI pipelines.
    you: not recommended
    AI recommended (in order):
    1. VQ-VAE
    2. VQ-GAN
    3. Diffusion Models
    4. Denoising Diffusion Probabilistic Models - DDPMs
    5. Latent Diffusion Models - LDMs
    6. Autoregressive Decoders
    7. PixelCNN
    8. Transformer-based decoders
    9. Adversarial VAEs (AVAEs)
    10. VAE-GANs
    11. Hierarchical VAEs
    12. NVAE
    13. HVAE
    14. Flow-based Decoders
    15. Glow
    16. RealNVP

    AI recommended 16 alternatives but never named openai/consistencydecoder. 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 openai/consistencydecoder?
    pass
    AI named openai/consistencydecoder explicitly

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

  • If a team adopts openai/consistencydecoder in production, what risks or prerequisites should they evaluate first?
    pass
    AI did not name openai/consistencydecoder — likely talking about a different project

    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 openai/consistencydecoder solve, and who is the primary audience?
    pass
    AI named openai/consistencydecoder explicitly

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

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openai/consistencydecoder — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite