RRepoGEO

REPOGEO REPORT · LITE

ibm-granite/granite-code-models

Default branch main · commit 4eaac8e5 · scanned 5/27/2026, 4:12:41 AM

GitHub: 1,250 stars · 82 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 ibm-granite/granite-code-models, 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
    code-llm, large-language-model, code-generation, code-intelligence, ai-ethics, ibm, foundation-model, apache-2.0, code-explanation, bug-fixing, code-translation
  • mediumreadme#2
    Add a concise, high-level summary statement at the top of the README

    Why:

    CURRENT
    The current README starts with a blank <p align="center"> block, followed by links, then the 'Introduction to Granite Code Models' heading.
    COPY-PASTE FIX
    Granite Code Models are a family of state-of-the-art open-source foundation models from IBM for code intelligence, excelling in generation, explanation, and bug fixing across 116 programming languages.
  • lowreadme#3
    Add a concise statement about enterprise-grade trustworthiness near the top of the README

    Why:

    CURRENT
    The 'Trustworthy Enterprise-Grade LLM' point is currently a bullet point under 'Key advantages' further down.
    COPY-PASTE FIX
    These models are built following IBM's AI Ethics principles, ensuring trustworthy enterprise usage.

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 ibm-granite/granite-code-models
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Code Llama
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Code Llama · recommended 1×
  2. DeepSeek Coder · recommended 1×
  3. StarCoder2 · recommended 1×
  4. Phind-CodeLlama · recommended 1×
  5. WizardCoder · recommended 1×
  • CATEGORY QUERY
    What open source large language models are best for various code generation tasks?
    you: not recommended
    AI recommended (in order):
    1. Code Llama
    2. DeepSeek Coder
    3. StarCoder2
    4. Phind-CodeLlama
    5. WizardCoder
    6. CodeGeeX2

    AI recommended 6 alternatives but never named ibm-granite/granite-code-models. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a robust AI model to assist with code explanation, bug fixing, and translation.
    you: not recommended
    AI recommended (in order):
    1. GPT-4
    2. Claude 3 Opus
    3. Gemini 1.5 Pro
    4. GPT-3.5 Turbo
    5. Code Llama (70B Instruct)
    6. Mixtral 8x7B Instruct

    AI recommended 6 alternatives but never named ibm-granite/granite-code-models. 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 ibm-granite/granite-code-models?
    pass
    AI named ibm-granite/granite-code-models explicitly

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

  • If a team adopts ibm-granite/granite-code-models in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ibm-granite/granite-code-models 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 ibm-granite/granite-code-models solve, and who is the primary audience?
    pass
    AI named ibm-granite/granite-code-models explicitly

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

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ibm-granite/granite-code-models — 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