RRepoGEO

REPOGEO REPORT · LITE

Blaizzy/mlx-vlm

Default branch main · commit 4a302899 · scanned 6/19/2026, 2:16:56 AM

GitHub: 5,072 stars · 598 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 Blaizzy/mlx-vlm, 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
  • mediumtopics#1
    Add key functionality topics

    Why:

    CURRENT
    apple-silicon, florence2, idefics, llava, llm, local-ai, mlx, molmo, paligemma, pixtral, vision-framework, vision-language-model, vision-transformer
    COPY-PASTE FIX
    apple-silicon, florence2, idefics, llava, llm, local-ai, mlx, molmo, paligemma, pixtral, vision-framework, vision-language-model, vision-transformer, fine-tuning, multimodal-ai
  • lowhomepage#2
    Add a homepage URL

    Why:

    COPY-PASTE FIX
    https://github.com/Blaizzy/mlx-vlm

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 Blaizzy/mlx-vlm
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PyTorch
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. PyTorch · recommended 1×
  2. Hugging Face Transformers · recommended 1×
  3. bitsandbytes · recommended 1×
  4. MLX · recommended 1×
  5. ONNX Runtime · recommended 1×
  • CATEGORY QUERY
    How can I run and fine-tune vision language models efficiently on my Apple Silicon Mac?
    you: not recommended
    AI recommended (in order):
    1. PyTorch
    2. Hugging Face Transformers
    3. bitsandbytes
    4. MLX
    5. ONNX Runtime
    6. Core ML
    7. coremltools
    8. TensorFlow
    9. tensorflow-metal

    AI recommended 9 alternatives but never named Blaizzy/mlx-vlm. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools allow local inference and serving of multimodal AI models, including vision and audio?
    you: not recommended
    AI recommended (in order):
    1. OpenVINO Toolkit (openvinotoolkit/openvino)
    2. ONNX Runtime (microsoft/onnxruntime)
    3. TensorFlow Lite (tensorflow/tensorflow)
    4. PyTorch Mobile (pytorch/pytorch)
    5. ML.NET (dotnet/machinelearning)
    6. DeepStream SDK (NVIDIA-AI-IOT/deepstream_sdk)
    7. Triton Inference Server (triton-inference-server/server)

    AI recommended 7 alternatives but never named Blaizzy/mlx-vlm. 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 Blaizzy/mlx-vlm?
    pass
    AI named Blaizzy/mlx-vlm explicitly

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

  • If a team adopts Blaizzy/mlx-vlm in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Blaizzy/mlx-vlm 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 Blaizzy/mlx-vlm solve, and who is the primary audience?
    pass
    AI named Blaizzy/mlx-vlm 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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MARKDOWN (README)
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Blaizzy/mlx-vlm — 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