REPOGEO REPORT · LITE

nunchaku-ai/ComfyUI-nunchaku

Default branch main · commit c71cc259 · scanned 5/10/2026, 11:17:11 AM

GitHub: 2,871 stars · 158 forks

AI VISIBILITY SCORE

40 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

2 pass · 0 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 nunchaku-ai/ComfyUI-nunchaku, 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 opening to emphasize ComfyUI integration for 4-bit inference

Why:

CURRENT

This repository provides the ComfyUI plugin for **Nunchaku**, an efficient inference engine for 4-bit neural networks quantized with SVDQuant.

COPY-PASTE FIX

This repository provides the **ComfyUI plugin for Nunchaku**, enabling efficient 4-bit inference for generative AI models, specifically leveraging SVDQuant for advanced quantization within ComfyUI's visual workflow environment.

mediumtopics#2

Add more specific topics related to ComfyUI and visual AI workflows

Why:

CURRENT

comfyui, diffusion, flux, genai, mlsys, quantization

COPY-PASTE FIX

comfyui, comfyui-nodes, visual-programming, ai-workflow, diffusion, genai, quantization, 4-bit-inference, svdquant

lowabout#3

Refine the 'About' description for clarity on ComfyUI integration

Why:

CURRENT

ComfyUI Plugin of Nunchaku

COPY-PASTE FIX

ComfyUI plugin for Nunchaku, enabling efficient 4-bit inference and SVDQuant quantization directly within ComfyUI's visual workflow.

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 nunchaku-ai/ComfyUI-nunchaku

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

pytorch/pytorch

Recommended in 3 of 2 queries

COMPETITOR LEADERBOARD

pytorch/pytorch · recommended 3×
NVIDIA TensorRT · recommended 2×
microsoft/onnxruntime · recommended 2×
huggingface/optimum · recommended 2×
openvinotoolkit/openvino · recommended 1×

CATEGORY QUERY
How to achieve efficient 4-bit inference for generative AI models in a visual workflow?
you: not recommended
AI recommended (in order):
1. NVIDIA TensorRT
2. ONNX Runtime (microsoft/onnxruntime)
3. OpenVINO Toolkit (openvinotoolkit/openvino)
4. OpenVINO Model Server (openvinotoolkit/model_server)
5. OpenVINO Notebooks (openvinotoolkit/openvino_notebooks)
6. Hugging Face Optimum (huggingface/optimum)
7. Hugging Face Transformers (huggingface/transformers)
8. Qualcomm AI Engine Direct (QNN)
9. MLIR (Multi-Level Intermediate Representation) (llvm/llvm-project)
10. Apache TVM (apache/tvm)
11. PyTorch 2.x (pytorch/pytorch)
12. `torch.compile` (pytorch/pytorch)
13. AOTInductor (pytorch/pytorch)
14. Torch-TensorRT (pytorch/TensorRT)
15. DeepSpeed-MII (Model Inference Interface) (microsoft/DeepSpeed-MII)
AI recommended 15 alternatives but never named nunchaku-ai/ComfyUI-nunchaku. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Looking for a tool to integrate 4-bit quantization for diffusion models into a workflow system.
you: not recommended
AI recommended (in order):
1. AutoGPTQ (AutoGPTQ/AutoGPTQ)
2. bitsandbytes (TimDettmers/bitsandbytes)
3. Optimum (huggingface/optimum)
4. NVIDIA TensorRT
5. ONNX Runtime (microsoft/onnxruntime)
AI recommended 5 alternatives but never named nunchaku-ai/ComfyUI-nunchaku. This is the gap to close.
Show full AI answer

Objective checks

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

Metadata completeness
pass
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 nunchaku-ai/ComfyUI-nunchaku?
pass
AI named nunchaku-ai/ComfyUI-nunchaku explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts nunchaku-ai/ComfyUI-nunchaku in production, what risks or prerequisites should they evaluate first?
pass
AI named nunchaku-ai/ComfyUI-nunchaku 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 nunchaku-ai/ComfyUI-nunchaku solve, and who is the primary audience?
pass
AI named nunchaku-ai/ComfyUI-nunchaku explicitly
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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Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/nunchaku-ai/ComfyUI-nunchaku.svg)](https://repogeo.com/en/r/nunchaku-ai/ComfyUI-nunchaku)

HTML

<a href="https://repogeo.com/en/r/nunchaku-ai/ComfyUI-nunchaku"><img src="https://repogeo.com/badge/nunchaku-ai/ComfyUI-nunchaku.svg" alt="RepoGEO" /></a>

Pro

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nunchaku-ai/ComfyUI-nunchaku — 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