RRepoGEO

REPOGEO REPORT · LITE

XiaomiMiMo/MiMo-V2-Flash

Default branch main · commit b4eaae40 · scanned 6/27/2026, 12:13:01 PM

GitHub: 1,350 stars · 63 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 XiaomiMiMo/MiMo-V2-Flash, 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
    Add a clear, concise LLM definition at the very top of the README

    Why:

    CURRENT
    The current README starts with branding images and navigation links before introducing the model's core purpose.
    COPY-PASTE FIX
    MiMo-V2-Flash is a Mixture-of-Experts (MoE) language model with 309B total parameters and 15B active parameters. Designed for high-speed reasoning and agentic workflows, it utilizes a novel hybrid attention architecture and Multi-Token Prediction (MTP) to achieve state-of-the-art performance while significantly reducing inference costs.
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://mimo.xiaomi.com/blog/mimo-v2-flash

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 XiaomiMiMo/MiMo-V2-Flash
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Claude 3 Opus
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Claude 3 Opus · recommended 2×
  2. GPT-4 · recommended 1×
  3. Gemini 1.5 Pro · recommended 1×
  4. Llama 3 · recommended 1×
  5. Mixtral 8x7B · recommended 1×
  • CATEGORY QUERY
    What are some efficient foundation models for complex reasoning tasks and agentic workflows?
    you: not recommended
    AI recommended (in order):
    1. GPT-4
    2. Claude 3 Opus
    3. Gemini 1.5 Pro
    4. Llama 3
    5. Mixtral 8x7B
    6. Cohere Command R+

    AI recommended 6 alternatives but never named XiaomiMiMo/MiMo-V2-Flash. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Which large language models provide high-speed inference for advanced coding and agentic applications?
    you: not recommended
    AI recommended (in order):
    1. GPT-4o
    2. Claude 3 Opus
    3. Claude 3 Sonnet
    4. Google Gemini 1.5 Pro
    5. Llama 3 70B Instruct
    6. Llama 3 8B Instruct
    7. Mixtral 8x7B Instruct
    8. Command R+

    AI recommended 8 alternatives but never named XiaomiMiMo/MiMo-V2-Flash. 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 XiaomiMiMo/MiMo-V2-Flash?
    pass
    AI named XiaomiMiMo/MiMo-V2-Flash explicitly

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

  • If a team adopts XiaomiMiMo/MiMo-V2-Flash in production, what risks or prerequisites should they evaluate first?
    pass
    AI named XiaomiMiMo/MiMo-V2-Flash 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 XiaomiMiMo/MiMo-V2-Flash solve, and who is the primary audience?
    pass
    AI did not name XiaomiMiMo/MiMo-V2-Flash — 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?

Embed your GEO score

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MARKDOWN (README)
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XiaomiMiMo/MiMo-V2-Flash — 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