RRepoGEO

REPOGEO REPORT · LITE

replit/ReplitLM

Default branch main · commit f95ecb74 · scanned 5/15/2026, 5:17:54 PM

GitHub: 1,062 stars · 132 forks

AI VISIBILITY SCORE
33 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 replit/ReplitLM, 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
    Reposition the README's opening to clearly state the model family's purpose

    Why:

    CURRENT
    # ReplitLM
Guides, code and configs for the ReplitLM model family.
    COPY-PASTE FIX
    # ReplitLM: A Family of State-of-the-Art Large Language Models for Code
Guides, inference code, and configurations for the ReplitLM model family, specifically designed for code generation, completion, and understanding.
  • hightopics#2
    Add more specific topics to improve categorization as a code LLM

    Why:

    CURRENT
    ai, ai4code, llm
    COPY-PASTE FIX
    ai, ai4code, llm, code-generation, code-completion, large-language-model, deep-learning, nlp, transformers, replit
  • mediumreadme#3
    Add a dedicated section or explicit mention of ReplitLM's core differentiators

    Why:

    COPY-PASTE FIX
    ## Why ReplitLM?
ReplitLM stands out for its compact size (e.g., 2.7B parameters) combined with specialized training on a massive, high-quality dataset of code and natural language from the Replit platform. This unique combination makes it highly efficient and performant for code-specific tasks, often outperforming larger models in code generation and completion benchmarks while being more accessible for fine-tuning and deployment.

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 replit/ReplitLM
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
JAX
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. JAX · recommended 2×
  2. Code Llama · recommended 1×
  3. DeepSeek Coder · recommended 1×
  4. StarCoder · recommended 1×
  5. StarCoder2 · recommended 1×
  • CATEGORY QUERY
    What are good open-source large language models for generating code snippets?
    you: not recommended
    AI recommended (in order):
    1. Code Llama
    2. DeepSeek Coder
    3. StarCoder
    4. StarCoder2
    5. Phind-CodeLlama
    6. WizardCoder
    7. Replit Code V1.5 3B

    AI recommended 7 alternatives but never named replit/ReplitLM. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I fine-tune a small language model for specialized code completion tasks?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. PEFT
    3. LoRA
    4. PyTorch
    5. PyTorch Lightning
    6. Keras
    7. TensorFlow
    8. JAX
    9. KerasNLP
    10. DeepSpeed
    11. JAX
    12. Flax

    AI recommended 12 alternatives but never named replit/ReplitLM. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • 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 replit/ReplitLM?
    pass
    AI did not name replit/ReplitLM — 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?

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

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

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite