RRepoGEO

REPOGEO REPORT · LITE

Tencent/TurboTransformers

Default branch master · commit 4fc7fb6b · scanned 5/18/2026, 1:07:21 PM

GitHub: 1,548 stars · 207 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
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 Tencent/TurboTransformers, 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's opening to emphasize specialized transformer inference

    Why:

    CURRENT
    The WeChat AI open-sourced TurboTransformers with the following characteristics.
    COPY-PASTE FIX
    TurboTransformers is a dedicated, high-performance inference engine for Transformer models (Bert, Albert, GPT2, Decoders, etc.) on CPU and GPU. Unlike general-purpose inference runtimes, TurboTransformers is purpose-built to deliver superior speed and usability specifically for transformer-based AI models, making transformers serving fast by adding a turbo to your inference engine!
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://turbotransformers.tencent.com
  • mediumlicense#3
    Clarify the existing license(s) directly in the README

    Why:

    COPY-PASTE FIX
    ## License
TurboTransformers is licensed under [Specify License Name(s) here, e.g., Apache 2.0 and MIT]. Please refer to the `LICENSE` file for full details.

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 Tencent/TurboTransformers
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 3 of 2 queries
COMPETITOR LEADERBOARD
  1. ONNX Runtime · recommended 3×
  2. OpenVINO · recommended 2×
  3. PyTorch · recommended 2×
  4. torch.compile (Dynamo) · recommended 2×
  5. BetterTransformer · recommended 2×
  • CATEGORY QUERY
    How to achieve significant speedup for transformer model inference on CPU and GPU?
    you: not recommended
    AI recommended (in order):
    1. OpenVINO
    2. ONNX Runtime
    3. PyTorch
    4. torch.compile (Dynamo)
    5. BetterTransformer
    6. TensorFlow Lite
    7. TVM (Apache TVM)
    8. NVIDIA TensorRT
    9. ONNX Runtime
    10. PyTorch
    11. torch.compile (Dynamo)
    12. BetterTransformer
    13. DeepSpeed
    14. TVM (Apache TVM)

    AI recommended 14 alternatives but never named Tencent/TurboTransformers. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are efficient runtimes for deploying large language models with variable input lengths?
    you: not recommended
    AI recommended (in order):
    1. vLLM
    2. NVIDIA TensorRT-LLM
    3. TGI (Text Generation Inference) by Hugging Face
    4. DeepSpeed-MII (Microsoft Inference Interface)
    5. ONNX Runtime
    6. OpenVINO
    7. TorchServe

    AI recommended 7 alternatives but never named Tencent/TurboTransformers. 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 Tencent/TurboTransformers?
    pass
    AI named Tencent/TurboTransformers explicitly

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

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