REPOGEO REPORT · LITE

rupeshs/fastsdcpu

Default branch main · commit e33c0f8c · scanned 5/22/2026, 1:54:43 PM

GitHub: 2,080 stars · 206 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 rupeshs/fastsdcpu, 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

Reposition README intro to emphasize AI PC/NPU and 'application' aspect

Why:

CURRENT

FastSD CPU is a faster version of Stable Diffusion on CPU. Based on Latent Consistency Models and Adversarial Diffusion Distillation.
The following interfaces are available :
- Desktop GUI, basic text to image generation (Qt,faster)
- WebUI (Advanced features,Lora,controlnet etc)
- CLI (CommandLine Interface)

COPY-PASTE FIX

FastSD CPU is a complete, high-performance application for running Stable Diffusion models on CPUs and Intel AI PCs with NPU acceleration. It offers a Desktop GUI, WebUI, and CLI, leveraging Latent Consistency Models and Adversarial Diffusion Distillation for rapid image generation.

mediumhomepage#2
Add a homepage URL to the repository's 'About' section
Why:
COPY-PASTE FIX
```
Add the official project homepage URL to the repository's 'About' section metadata.
```

mediumcomparison#3

Add a 'Comparison' section to the README

Why:

COPY-PASTE FIX

Add a new section to the README, e.g., '## Comparison with other Stable Diffusion UIs', detailing how FastSD CPU excels in CPU/NPU performance compared to GPU-centric alternatives like Automatic1111 or ComfyUI.

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 rupeshs/fastsdcpu

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

AUTOMATIC1111/stable-diffusion-webui

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

AUTOMATIC1111/stable-diffusion-webui · recommended 1×
invoke-ai/InvokeAI · recommended 1×
huggingface/diffusers · recommended 1×
microsoft/onnxruntime · recommended 1×
comfyanonymous/ComfyUI · recommended 1×

CATEGORY QUERY
How to run stable diffusion models quickly on a local CPU without dedicated GPU?
you: not recommended
AI recommended (in order):
1. Automatic1111's Stable Diffusion WebUI (AUTOMATIC1111/stable-diffusion-webui)
2. InvokeAI (invoke-ai/InvokeAI)
3. Diffusers Library (huggingface/diffusers)
4. ONNX Runtime (microsoft/onnxruntime)
5. ComfyUI (comfyanonymous/ComfyUI)
6. PyTorch (pytorch/pytorch)
7. TensorFlow (tensorflow/tensorflow)
AI recommended 7 alternatives but never named rupeshs/fastsdcpu. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What tools enable fast AI image generation on an Intel AI PC with NPU acceleration?
you: not recommended
AI recommended (in order):
1. Automatic1111 Stable Diffusion web UI
2. ComfyUI
3. InvokeAI
4. Fooocus
5. Diffusers
6. Intel Extension for PyTorch
AI recommended 6 alternatives but never named rupeshs/fastsdcpu. 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 rupeshs/fastsdcpu?
pass
AI named rupeshs/fastsdcpu explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts rupeshs/fastsdcpu in production, what risks or prerequisites should they evaluate first?
pass
AI named rupeshs/fastsdcpu 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 rupeshs/fastsdcpu solve, and who is the primary audience?
pass
AI did not name rupeshs/fastsdcpu — 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

Drop this badge into the README of rupeshs/fastsdcpu. 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)

[![RepoGEO](https://repogeo.com/badge/rupeshs/fastsdcpu.svg)](https://repogeo.com/en/r/rupeshs/fastsdcpu)

HTML

<a href="https://repogeo.com/en/r/rupeshs/fastsdcpu"><img src="https://repogeo.com/badge/rupeshs/fastsdcpu.svg" alt="RepoGEO" /></a>

Pro

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rupeshs/fastsdcpu — 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