RRepoGEO

REPOGEO REPORT · LITE

madebyollin/maple-diffusion

Default branch main · commit 6304d68a · scanned 6/14/2026, 11:38:15 PM

GitHub: 819 stars · 53 forks

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 madebyollin/maple-diffusion, 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 for discoverability

    Why:

    COPY-PASTE FIX
    stable-diffusion, ios, macos, swift, mpsgraph, apple-silicon, on-device-inference, machine-learning
  • highreadme#2
    Strengthen README opening to highlight core value proposition

    Why:

    CURRENT
    # 🍁 Maple Diffusion

Maple Diffusion runs Stable Diffusion models **locally** on macOS / iOS devices, in Swift, using the MPSGraph framework (not Python).
    COPY-PASTE FIX
    # 🍁 Maple Diffusion

Maple Diffusion is a highly performant, native Swift implementation for running Stable Diffusion models **locally** on macOS / iOS devices, leveraging Apple's MPSGraph framework for optimal on-device inference (no Python required).
  • mediumreadme#3
    Add a clear 'Why Maple Diffusion?' or 'Comparison' section

    Why:

    COPY-PASTE FIX
    ## Why Choose Maple Diffusion?

While projects like Core ML Stable Diffusion offer similar functionality, Maple Diffusion distinguishes itself by directly utilizing MPSGraph for fine-grained control and performance optimizations, often achieving faster inference speeds on specific Apple hardware configurations. It's ideal for developers seeking maximum performance and direct Metal integration without relying on higher-level frameworks like Core ML.

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 madebyollin/maple-diffusion
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Core ML Stable Diffusion
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Core ML Stable Diffusion · recommended 1×
  2. diffusers · recommended 1×
  3. ML-Stable-Diffusion · recommended 1×
  4. ONNX Runtime · recommended 1×
  5. PyTorch Mobile · recommended 1×
  • CATEGORY QUERY
    What are the options for running Stable Diffusion locally on iOS/macOS using Swift?
    you: not recommended
    AI recommended (in order):
    1. Core ML Stable Diffusion
    2. diffusers
    3. ML-Stable-Diffusion
    4. ONNX Runtime
    5. PyTorch Mobile

    AI recommended 5 alternatives but never named madebyollin/maple-diffusion. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a performant solution for on-device Stable Diffusion inference on Apple mobile hardware.
    you: not recommended
    AI recommended (in order):
    1. Core ML with Stable Diffusion
    2. MLX (apple/mlx)
    3. ONNX Runtime (microsoft/onnxruntime)
    4. TFLite (TensorFlow Lite) (tensorflow/tensorflow)
    5. PyTorch Mobile (pytorch/pytorch)

    AI recommended 5 alternatives but never named madebyollin/maple-diffusion. 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 madebyollin/maple-diffusion?
    pass
    AI did not name madebyollin/maple-diffusion — 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 madebyollin/maple-diffusion in production, what risks or prerequisites should they evaluate first?
    pass
    AI named madebyollin/maple-diffusion 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 madebyollin/maple-diffusion solve, and who is the primary audience?
    pass
    AI named madebyollin/maple-diffusion 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 madebyollin/maple-diffusion. 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/madebyollin/maple-diffusion.svg)](https://repogeo.com/en/r/madebyollin/maple-diffusion)
HTML
<a href="https://repogeo.com/en/r/madebyollin/maple-diffusion"><img src="https://repogeo.com/badge/madebyollin/maple-diffusion.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

madebyollin/maple-diffusion — 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