RRepoGEO

REPOGEO REPORT · LITE

ByteVisionLab/DreamLite

Default branch main · commit 077ce0a5 · scanned 5/31/2026, 1:53:03 PM

GitHub: 674 stars · 44 forks

AI VISIBILITY SCORE
35 /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
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 ByteVisionLab/DreamLite, 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 specific topics for on-device AI models

    Why:

    COPY-PASTE FIX
    on-device-ai, mobile-ai, diffusion-model, image-generation, image-editing, lightweight-model, edge-ai, unified-model
  • highhomepage#2
    Add the project homepage URL to the repo's About section

    Why:

    COPY-PASTE FIX
    https://carlofkl.github.io/dreamlite/
  • mediumreadme#3
    Strengthen the 'Overview' opening sentence to emphasize 'model' and 'on-device'

    Why:

    CURRENT
    We introduce **DreamLite**, a compact and unified on-device diffusion model (**0.39B**) that seamlessly supports both **text-to-image generation** and **text-guided image editing** within a single network architecture.
    COPY-PASTE FIX
    **DreamLite** is a compact, unified, and *fully on-device* diffusion *model* (**0.39B**) designed for seamless **text-to-image generation** and **text-guided image editing** within a single network architecture, eliminating cloud dependency.

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 ByteVisionLab/DreamLite
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Core ML
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Core ML · recommended 1×
  2. TensorFlow Lite · recommended 1×
  3. ONNX Runtime Mobile · recommended 1×
  4. Hugging Face Diffusers · recommended 1×
  5. MediaPipe · recommended 1×
  • CATEGORY QUERY
    How to run a lightweight image generation and editing model directly on mobile devices?
    you: not recommended
    AI recommended (in order):
    1. Core ML
    2. TensorFlow Lite
    3. ONNX Runtime Mobile
    4. Hugging Face Diffusers
    5. MediaPipe
    6. PyTorch Mobile
    7. MLX

    AI recommended 7 alternatives but never named ByteVisionLab/DreamLite. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a fast unified model for text-to-image generation and text-guided editing without cloud.
    you: not recommended
    AI recommended (in order):
    1. Automatic1111 web UI (AUTOMATIC1111/stable-diffusion-webui)
    2. ComfyUI (comfyanonymous/ComfyUI)
    3. Fooocus (lllyasviel/Fooocus)
    4. InvokeAI (invoke-ai/InvokeAI)
    5. Diffusers (huggingface/diffusers)
    6. SD.Next (vladmandic/automatic)

    AI recommended 6 alternatives but never named ByteVisionLab/DreamLite. 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 ByteVisionLab/DreamLite?
    pass
    AI named ByteVisionLab/DreamLite explicitly

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

  • If a team adopts ByteVisionLab/DreamLite in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ByteVisionLab/DreamLite 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 ByteVisionLab/DreamLite solve, and who is the primary audience?
    pass
    AI named ByteVisionLab/DreamLite 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 ByteVisionLab/DreamLite. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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ByteVisionLab/DreamLite — 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