RRepoGEO

REPOGEO REPORT · LITE

open-compass/MixtralKit

Default branch main · commit d4da9e05 · scanned 6/14/2026, 3:57:35 AM

GitHub: 773 stars · 75 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 open-compass/MixtralKit, 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 H1 to specify category and focus

    Why:

    CURRENT
    # MixtralKit

A Toolkit for Mixtral Model
    COPY-PASTE FIX
    # MixtralKit: A Specialized Toolkit for Mixtral-8x7B Inference and Evaluation
  • hightopics#2
    Add more specific topics to improve categorization

    Why:

    CURRENT
    llm, mistral, moe
    COPY-PASTE FIX
    llm, mistral, moe, inference, evaluation, benchmarking, mixtral-8x7b
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/open-compass/opencompass

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 open-compass/MixtralKit
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
microsoft/DeepSpeed
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. microsoft/DeepSpeed · recommended 1×
  2. facebookresearch/fairseq · recommended 1×
  3. huggingface/transformers · recommended 1×
  4. vllm-project/vllm · recommended 1×
  5. triton-inference-server/server · recommended 1×
  • CATEGORY QUERY
    How to run inference and evaluate Mixture of Experts (MoE) large language models?
    you: not recommended
    AI recommended (in order):
    1. DeepSpeed (microsoft/DeepSpeed)
    2. Fairseq (facebookresearch/fairseq)
    3. Hugging Face Transformers (huggingface/transformers)
    4. vLLM (vllm-project/vllm)
    5. Triton Inference Server (triton-inference-server/server)
    6. TensorRT-LLM (NVIDIA/TensorRT-LLM)
    7. OpenVINO (openvinotoolkit/openvino)

    AI recommended 7 alternatives but never named open-compass/MixtralKit. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a toolkit for efficient inference and performance evaluation of Mistral-style LLMs.
    you: not recommended
    AI recommended (in order):
    1. vLLM
    2. TGI (Text Generation Inference)
    3. TensorRT-LLM
    4. Ollama
    5. LMDeploy
    6. Hugging Face `transformers`
    7. `bitsandbytes`
    8. `accelerate`

    AI recommended 8 alternatives but never named open-compass/MixtralKit. 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 open-compass/MixtralKit?
    pass
    AI named open-compass/MixtralKit explicitly

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

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

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

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open-compass/MixtralKit — 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