RRepoGEO

REPOGEO REPORT · LITE

lllyasviel/ControlNet-v1-1-nightly

Default branch main · commit e2b44154 · scanned 6/26/2026, 9:08:23 PM

GitHub: 5,164 stars · 408 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
17 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
1 / 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 lllyasviel/ControlNet-v1-1-nightly, 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
  • hightopics#1
    Add relevant topics to improve categorization

    Why:

    COPY-PASTE FIX
    diffusion-models, controlnet, image-generation, ai-art, computer-vision, deep-learning, stable-diffusion, research-project, nightly-build
  • highreadme#2
    Clarify the README's opening statement to emphasize research focus

    Why:

    CURRENT
    # ControlNet 1.1

This is the official release of ControlNet 1.1.

ControlNet 1.1 has the exactly same architecture with ControlNet 1.0.
    COPY-PASTE FIX
    # ControlNet 1.1: Nightly Release for Research and Academic Experiments

This is the official nightly release of ControlNet 1.1, primarily intended for researchers and academic experiments. ControlNet 1.1 maintains the same architecture as ControlNet 1.0, offering improved robustness and result quality with several new models.
  • highlicense#3
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the root of the repository with the appropriate license text (e.g., MIT, Apache-2.0, or a custom license if applicable).

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 lllyasviel/ControlNet-v1-1-nightly
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ControlNet
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ControlNet · recommended 2×
  2. IP-Adapter · recommended 2×
  3. MiDaS · recommended 1×
  4. LeReS · recommended 1×
  5. OpenPose · recommended 1×
  • CATEGORY QUERY
    How can I get more precise control over generated images from diffusion models?
    you: not recommended
    AI recommended (in order):
    1. ControlNet
    2. MiDaS
    3. LeReS
    4. OpenPose
    5. PidiNet
    6. IP-Adapter
    7. Automatic1111
    8. ComfyUI
    9. Fooocus

    AI recommended 9 alternatives but never named lllyasviel/ControlNet-v1-1-nightly. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the latest advancements for fine-tuning image generation with neural networks?
    you: not recommended
    AI recommended (in order):
    1. LoRA
    2. QLoRA
    3. LoRAX
    4. DreamBooth LoRA
    5. ControlNet
    6. IP-Adapter
    7. StyleGAN-XL
    8. T2I-Adapter
    9. GLIGEN

    AI recommended 9 alternatives but never named lllyasviel/ControlNet-v1-1-nightly. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 lllyasviel/ControlNet-v1-1-nightly?
    pass
    AI did not name lllyasviel/ControlNet-v1-1-nightly — 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?

  • If a team adopts lllyasviel/ControlNet-v1-1-nightly in production, what risks or prerequisites should they evaluate first?
    pass
    AI named lllyasviel/ControlNet-v1-1-nightly 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 lllyasviel/ControlNet-v1-1-nightly solve, and who is the primary audience?
    pass
    AI did not name lllyasviel/ControlNet-v1-1-nightly — 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?

Embed your GEO score

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lllyasviel/ControlNet-v1-1-nightly — 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