RRepoGEO

REPOGEO REPORT · LITE

MoonshotAI/Kimi-k1.5

Default branch main · commit cf9a8785 · scanned 5/15/2026, 12:42:50 AM

GitHub: 3,474 stars · 234 forks

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 MoonshotAI/Kimi-k1.5, 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
  • highabout#1
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    Kimi k1.5 is an o1-level multi-modal large language model excelling in complex reasoning, math, and coding benchmarks, featuring a 128k long context window and advanced RL scaling techniques.
  • hightopics#2
    Add specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    multi-modal-llm, large-language-model, reinforcement-learning, long-context, ai-model, deep-learning, math-benchmarks, coding-benchmarks
  • mediumlicense#3
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the root of the repository with the appropriate open-source license text.

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 MoonshotAI/Kimi-k1.5
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
GPT-4o
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. GPT-4o · recommended 1×
  2. Gemini 1.5 Pro · recommended 1×
  3. Claude 3 Opus · recommended 1×
  4. Llama 3 · recommended 1×
  5. LLaVA · recommended 1×
  • CATEGORY QUERY
    Which multi-modal LLMs offer superior performance in complex reasoning, math, and coding benchmarks?
    you: not recommended
    AI recommended (in order):
    1. GPT-4o
    2. Gemini 1.5 Pro
    3. Claude 3 Opus
    4. Llama 3
    5. LLaVA
    6. Fuyu-8B
    7. Qwen-VL-Plus

    AI recommended 7 alternatives but never named MoonshotAI/Kimi-k1.5. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I efficiently scale reinforcement learning with LLMs, especially with very long context windows?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face TRL
    2. Hugging Face PEFT
    3. LoRA
    4. QLoRA
    5. DeepSpeed
    6. FSDP
    7. Ray RLlib
    8. vLLM
    9. Hugging Face TGI
    10. Pinecone
    11. Weaviate
    12. Chroma
    13. Anthropic Claude 3
    14. OpenAI GPT-4 Turbo
    15. Google Gemini 1.5 Pro
    16. Meta Llama 3
    17. FlashAttention
    18. xFormers

    AI recommended 18 alternatives but never named MoonshotAI/Kimi-k1.5. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 MoonshotAI/Kimi-k1.5?
    pass
    AI named MoonshotAI/Kimi-k1.5 explicitly

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

  • If a team adopts MoonshotAI/Kimi-k1.5 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named MoonshotAI/Kimi-k1.5 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 MoonshotAI/Kimi-k1.5 solve, and who is the primary audience?
    pass
    AI named MoonshotAI/Kimi-k1.5 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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MoonshotAI/Kimi-k1.5 — 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