RRepoGEO

REPOGEO REPORT · LITE

deepseek-ai/open-infra-index

Default branch main · commit 56d86855 · scanned 5/25/2026, 11:08:21 PM

GitHub: 7,999 stars · 288 forks

AI VISIBILITY SCORE
22 /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
1 / 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 deepseek-ai/open-infra-index, 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 specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    ai-infrastructure, agi, deep-learning, gpu-acceleration, llm-inference, production-ready, open-source-ai, deepseek
  • highreadme#2
    Add a concise introductory sentence to the README

    Why:

    CURRENT
    # Hello, DeepSeek Open Infra!

## 202505 Industry Track Paper (ISCA25)
    COPY-PASTE FIX
    # Hello, DeepSeek Open Infra!

This repository serves as a central hub for DeepSeek's production-tested AI infrastructure tools, designed for efficient AGI development and community-driven innovation.

## 202505 Industry Track Paper (ISCA25)
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    [Insert DeepSeek AI's main open-source or project page URL here]

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 deepseek-ai/open-infra-index
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ray-project/ray
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ray-project/ray · recommended 2×
  2. Kubernetes · recommended 1×
  3. Kubeflow · recommended 1×
  4. AWS SageMaker · recommended 1×
  5. Google Cloud Vertex AI · recommended 1×
  • CATEGORY QUERY
    Seeking production-ready infrastructure for efficient AGI model deployment and scaling.
    you: not recommended
    AI recommended (in order):
    1. Kubernetes
    2. Kubeflow
    3. AWS SageMaker
    4. Google Cloud Vertex AI
    5. Azure Machine Learning
    6. Hugging Face Inference Endpoints
    7. TGI (Text Generation Inference) (huggingface/text-generation-inference)
    8. Ray (ray-project/ray)
    9. Ray Serve (ray-project/ray)
    10. MLflow (mlflow/mlflow)
    11. Databricks

    AI recommended 11 alternatives but never named deepseek-ai/open-infra-index. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to improve large language model decoding performance on modern accelerators?
    you: not recommended
    AI recommended (in order):
    1. NVIDIA TensorRT-LLM
    2. vLLM
    3. DeepSpeed-MII
    4. Hugging Face Optimum
    5. ONNX Runtime
    6. OpenVINO
    7. Habana Gaudi
    8. Triton Inference Server
    9. FlashAttention
    10. FlashAttention-2
    11. llama.cpp

    AI recommended 11 alternatives but never named deepseek-ai/open-infra-index. 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 deepseek-ai/open-infra-index?
    pass
    AI did not name deepseek-ai/open-infra-index — 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 deepseek-ai/open-infra-index in production, what risks or prerequisites should they evaluate first?
    pass
    AI named deepseek-ai/open-infra-index 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 deepseek-ai/open-infra-index solve, and who is the primary audience?
    pass
    AI did not name deepseek-ai/open-infra-index — 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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  • Brand-free category queries5 vs 2 in Lite
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