RRepoGEO

REPOGEO REPORT · LITE

anomalyco/models.dev

Default branch dev · commit 8cbf6ed1 · scanned 5/9/2026, 7:07:43 AM

GitHub: 3,723 stars · 935 forks

AI VISIBILITY SCORE
28 /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
2 / 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 anomalyco/models.dev, 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
    Clarify repo's role as a model database, not a provider, and confirm its usage

    Why:

    CURRENT
    Models.dev is a comprehensive open-source database of AI model specifications, pricing, and capabilities.
    COPY-PASTE FIX
    Models.dev is a comprehensive open-source database of AI model specifications, pricing, and capabilities. Unlike AI model providers or platforms, Models.dev focuses on aggregating and standardizing information *about* these models, not providing access to them directly. We use this data internally at opencode, and it's designed to be a reliable, community-contributed resource.
  • mediumreadme#2
    Add a 'Why Models.dev?' section to clarify its unique value and audience

    Why:

    COPY-PASTE FIX
    ## Why Models.dev?

There's no single, up-to-date database with comprehensive information about all the available AI models, their specifications, and pricing. Models.dev fills this gap by providing a community-contributed, open-source data source. Our goal is to empower developers, researchers, and businesses to make informed decisions about AI model selection without sifting through countless provider documentations.

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 anomalyco/models.dev
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Azure OpenAI Service
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Azure OpenAI Service · recommended 2×
  2. OpenAI · recommended 1×
  3. Anthropic Claude · recommended 1×
  4. Google Cloud AI · recommended 1×
  5. Vertex AI · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive list of AI model capabilities and pricing details?
    you: not recommended
    AI recommended (in order):
    1. OpenAI
    2. Anthropic Claude
    3. Google Cloud AI
    4. Vertex AI
    5. Hugging Face Hub
    6. Amazon Bedrock
    7. Amazon SageMaker
    8. Microsoft Azure AI Services
    9. Azure OpenAI Service
    10. AI21 Labs
    11. Wordtune
    12. DALL-E 3
    13. Midjourney
    14. Stable Diffusion
    15. Google Imagen
    16. Whisper
    17. Google Speech-to-Text
    18. AWS Transcribe
    19. Everyprompt
    20. Vercel AI SDK

    AI recommended 20 alternatives but never named anomalyco/models.dev. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need an API to programmatically access specifications and costs for different large language models.
    you: not recommended
    AI recommended (in order):
    1. OpenAI API
    2. Anthropic API
    3. Google Cloud Vertex AI
    4. Hugging Face Inference API
    5. Azure OpenAI Service
    6. Cohere API
    7. AWS Bedrock

    AI recommended 7 alternatives but never named anomalyco/models.dev. 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 anomalyco/models.dev?
    pass
    AI named anomalyco/models.dev explicitly

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

  • If a team adopts anomalyco/models.dev in production, what risks or prerequisites should they evaluate first?
    pass
    AI did not name anomalyco/models.dev — likely talking about a different project

    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 anomalyco/models.dev solve, and who is the primary audience?
    pass
    AI named anomalyco/models.dev 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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