RRepoGEO

REPOGEO REPORT · LITE

MDK8888/GPTFast

Default branch master · commit 926b7553 · scanned 6/5/2026, 8:32:03 PM

GitHub: 683 stars · 64 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 MDK8888/GPTFast, 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
  • highreadme#1
    Remove or update the deprecated documentation warning in 'Getting Started'

    Why:

    CURRENT
    ## WARNING: The below documentation is now deprecated with version 0.3.0. New docs will be up soon! ##
    COPY-PASTE FIX
    ## Getting Started (New documentation for v0.3.0+ coming soon!) ##
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    [Your project's official documentation or website URL here]

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 MDK8888/GPTFast
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ONNX Runtime
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. ONNX Runtime · recommended 1×
  2. NVIDIA TensorRT · recommended 1×
  3. OpenVINO · recommended 1×
  4. DeepSpeed-MII · recommended 1×
  5. bitsandbytes · recommended 1×
  • CATEGORY QUERY
    How can I significantly speed up inference for my Hugging Face transformer models?
    you: not recommended
    AI recommended (in order):
    1. ONNX Runtime
    2. NVIDIA TensorRT
    3. OpenVINO
    4. DeepSpeed-MII
    5. bitsandbytes
    6. AWQ
    7. GPTQ
    8. FlashAttention
    9. xFormers
    10. TorchScript

    AI recommended 10 alternatives but never named MDK8888/GPTFast. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are effective PyTorch-native methods to optimize large language model inference speed?
    you: not recommended
    AI recommended (in order):
    1. torch.compile
    2. Quantization
    3. FlashAttention (Dao-AILab/flash-attention)
    4. BetterTransformer
    5. Half-precision Inference
    6. Model Tracing
    7. torch.inference_mode()

    AI recommended 7 alternatives but never named MDK8888/GPTFast. 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 MDK8888/GPTFast?
    pass
    AI named MDK8888/GPTFast explicitly

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

  • If a team adopts MDK8888/GPTFast in production, what risks or prerequisites should they evaluate first?
    pass
    AI named MDK8888/GPTFast 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 MDK8888/GPTFast solve, and who is the primary audience?
    pass
    AI named MDK8888/GPTFast explicitly

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

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MDK8888/GPTFast — 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