RRepoGEO

REPOGEO REPORT · LITE

welltop-cn/ComfyUI-TeaCache

Default branch main · commit 91dff8e3 · scanned 5/15/2026, 5:03:04 AM

GitHub: 1,083 stars · 66 forks

AI VISIBILITY SCORE
30 /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
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 welltop-cn/ComfyUI-TeaCache, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highabout#1
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    A ComfyUI extension that implements Timestep Embedding Aware Cache (TeaCache) for accelerating inference in Image, Video, and Audio Diffusion models with training-free caching.
  • mediumhomepage#2
    Add a homepage URL to the repository

    Why:

    COPY-PASTE FIX
    https://github.com/welltop-cn/ComfyUI-TeaCache#readme

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 welltop-cn/ComfyUI-TeaCache
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
NVIDIA TensorRT
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. NVIDIA TensorRT · recommended 1×
  2. OpenVINO · recommended 1×
  3. ONNX Runtime · recommended 1×
  4. PyTorch Quantization APIs · recommended 1×
  5. XLA · recommended 1×
  • CATEGORY QUERY
    What are effective techniques to speed up image and video diffusion model inference?
    you: not recommended
    AI recommended (in order):
    1. NVIDIA TensorRT
    2. OpenVINO
    3. ONNX Runtime
    4. PyTorch Quantization APIs
    5. XLA
    6. TorchInductor
    7. DDIM
    8. DPM-Solver
    9. PLMS
    10. Euler Ancestral / Euler Discrete
    11. NVIDIA GPUs
    12. Google TPUs
    13. Intel Gaudi Accelerators
    14. Apple Neural Engine
    15. Stable Diffusion
    16. Progressive Distillation
    17. PyTorch DataLoader
    18. torch.nn.DataParallel
    19. torch.nn.parallel.DistributedDataParallel
    20. Gradient Checkpointing
    21. FlashAttention

    AI recommended 21 alternatives but never named welltop-cn/ComfyUI-TeaCache. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I accelerate diffusion model generation using a training-free caching approach?
    you: not recommended
    AI recommended (in order):
    1. Diffusers Library (huggingface/diffusers)
    2. ONNX Runtime (microsoft/onnxruntime)
    3. TensorRT
    4. DeepSpeed-MII (microsoft/DeepSpeed-MII)
    5. Optimum (huggingface/optimum)
    6. OpenVINO (openvinotoolkit/openvino)
    7. TorchDynamo (pytorch/pytorch)
    8. xFormers (facebookresearch/xformers)
    9. FlashAttention-2 (Dao-AILab/flash-attention)

    AI recommended 9 alternatives but never named welltop-cn/ComfyUI-TeaCache. 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 welltop-cn/ComfyUI-TeaCache?
    pass
    AI named welltop-cn/ComfyUI-TeaCache explicitly

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

  • If a team adopts welltop-cn/ComfyUI-TeaCache in production, what risks or prerequisites should they evaluate first?
    pass
    AI named welltop-cn/ComfyUI-TeaCache 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 welltop-cn/ComfyUI-TeaCache solve, and who is the primary audience?
    pass
    AI named welltop-cn/ComfyUI-TeaCache 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 welltop-cn/ComfyUI-TeaCache. 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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welltop-cn/ComfyUI-TeaCache — 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