RRepoGEO

REPOGEO REPORT · LITE

deepseek-ai/DeepSeek-VL2

Default branch main · commit ef9f91e2 · scanned 5/15/2026, 5:33:36 PM

GitHub: 5,283 stars · 1,814 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 deepseek-ai/DeepSeek-VL2, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    vision-language-model, multimodal-ai, mixture-of-experts, large-language-model, deep-learning, ai-model, computer-vision, natural-language-processing, llm, vlm
  • mediumhomepage#2
    Set a homepage URL for the repository

    Why:

    COPY-PASTE FIX
    https://huggingface.co/spaces/deepseek-ai/deepseek-vl2-small
  • lowreadme#3
    Clarify the dual license structure in the README's license section

    Why:

    COPY-PASTE FIX
    Add to the '5. License' section: 'This project uses a dual licensing approach: the code is licensed under MIT, while the DeepSeek-VL2 models are licensed under the DeepSeek-VL2 Model License.'

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 deepseek-ai/DeepSeek-VL2
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Llama 2
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Llama 2 · recommended 2×
  2. LLaVA · recommended 2×
  3. OpenAI GPT-4V (Vision) · recommended 1×
  4. Google Gemini (Pro/Ultra) · recommended 1×
  5. Llama 3 · recommended 1×
  • CATEGORY QUERY
    How to integrate a model that understands both images and text for complex reasoning tasks?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-4V (Vision)
    2. Google Gemini (Pro/Ultra)
    3. Llama 3
    4. CLIP (Contrastive Language-Image Pre-training)
    5. Llama 2
    6. Mistral
    7. BLIP-2 (Bootstrapping Language-Image Pre-training with Frozen Latents)
    8. ViLT (Vision-and-Language Transformer)
    9. InstructBLIP
    10. LLaVA

    AI recommended 10 alternatives but never named deepseek-ai/DeepSeek-VL2. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best open source mixture-of-experts models for multimodal AI applications?
    you: not recommended
    AI recommended (in order):
    1. Mixtral 8x7B
    2. CLIP
    3. LLaVA
    4. DeepSeek-MoE
    5. Qwen1.5-MoE
    6. Llama 2
    7. Hugging Face's Transformers library
    8. arXiv

    AI recommended 8 alternatives but never named deepseek-ai/DeepSeek-VL2. 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 deepseek-ai/DeepSeek-VL2?
    pass
    AI named deepseek-ai/DeepSeek-VL2 explicitly

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

  • If a team adopts deepseek-ai/DeepSeek-VL2 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named deepseek-ai/DeepSeek-VL2 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 deepseek-ai/DeepSeek-VL2 solve, and who is the primary audience?
    pass
    AI named deepseek-ai/DeepSeek-VL2 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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deepseek-ai/DeepSeek-VL2 — 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