RRepoGEO

REPOGEO REPORT · LITE

QwenLM/qwen.cpp

Default branch master · commit e532c24d · scanned 6/10/2026, 5:37:47 PM

GitHub: 627 stars · 64 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 QwenLM/qwen.cpp, 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
    Add a concise project summary before the deprecation notice

    Why:

    CURRENT
    > [!IMPORTANT]
    >
    > **End of Active Maintenance for qwen.cpp**
    > 
    > Since December 2023, the core features of qwen.cpp have been integrated into llama.cpp. As of December 2024, qwen.cpp no longer offers the same level of functionality, efficiency, and device support as llama.cpp, including updates to newer Qwen models.
    >
    > We regret to announce that we will no longer actively maintain qwen.cpp. This means we will not be addressing issues, merging pull requests, or releasing updates. For ongoing development and support, we encourage you to explore llama.cpp, which continues to evolve with new features and improvements.
    >
    > Thank you for being part of our journey.
    
    # qwen.cpp
    
    C++ implementation of Qwen-LM for real-time chatting on your MacBook.
    COPY-PASTE FIX
    # qwen.cpp: The original C++ implementation of Qwen-LM
    
    This repository provides the foundational C++ implementation of Qwen-LM, enabling real-time inference on various hardware. While its core features have been integrated into llama.cpp for ongoing development, qwen.cpp remains a historical reference for the initial C++ port.
    
    > [!IMPORTANT]
    >
    > **End of Active Maintenance for qwen.cpp**
    > 
    > Since December 2023, the core features of qwen.cpp have been integrated into llama.cpp. As of December 2024, qwen.cpp no longer offers the same level of functionality, efficiency, and device support as llama.cpp, including updates to newer Qwen models.
    >
    > We regret to announce that we will no longer actively maintain qwen.cpp. This means we will not be addressing issues, merging pull requests, or releasing updates. For ongoing development and support, we encourage you to explore llama.cpp, which continues to evolve with new features and improvements.
    >
    > Thank you for being part of our journey.
  • mediumhomepage#2
    Add a homepage URL pointing to the successor project

    Why:

    COPY-PASTE FIX
    https://github.com/ggerganov/llama.cpp
  • lowreadme#3
    Clarify the project's license(s) in the README

    Why:

    COPY-PASTE FIX
    ## License
    
    This project is licensed under [Specify License Name(s) here, e.g., Apache-2.0 and MIT]. Please refer to the [LICENSE](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 QwenLM/qwen.cpp
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ggerganov/llama.cpp
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ggerganov/llama.cpp · recommended 2×
  2. openvinotoolkit/openvino · recommended 2×
  3. microsoft/onnxruntime · recommended 2×
  4. ggerganov/ggml · recommended 1×
  5. Tencent/ncnn · recommended 1×
  • CATEGORY QUERY
    How can I run large language models on CPU with C++ for real-time inference?
    you: not recommended
    AI recommended (in order):
    1. llama.cpp (ggerganov/llama.cpp)
    2. OpenVINO (openvinotoolkit/openvino)
    3. ONNX Runtime (microsoft/onnxruntime)
    4. GGML (ggerganov/ggml)
    5. ncnn (Tencent/ncnn)
    6. DirectML (Microsoft/DirectML)

    AI recommended 6 alternatives but never named QwenLM/qwen.cpp. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a C++ library to integrate streaming LLM inference into desktop applications.
    you: not recommended
    AI recommended (in order):
    1. llama.cpp (ggerganov/llama.cpp)
    2. OpenVINO Toolkit (openvinotoolkit/openvino)
    3. ONNX Runtime (microsoft/onnxruntime)
    4. TensorRT (NVIDIA/TensorRT)
    5. libtorch (pytorch/pytorch)
    6. MLX (ml-explore/mlx)

    AI recommended 6 alternatives but never named QwenLM/qwen.cpp. 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 QwenLM/qwen.cpp?
    pass
    AI named QwenLM/qwen.cpp explicitly

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

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

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

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QwenLM/qwen.cpp — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite
QwenLM/qwen.cpp — RepoGEO report