RRepoGEO

REPOGEO REPORT · LITE

groq/openbench

Default branch main · commit f8e643bc · scanned 6/2/2026, 7:42:10 AM

GitHub: 776 stars · 101 forks

AI VISIBILITY SCORE
40 /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
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 groq/openbench, 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 comprehensive LLM evaluation topics

    Why:

    CURRENT
    managed-by-terraform
    COPY-PASTE FIX
    ["llm-evaluation", "llm-benchmarking", "language-models", "generative-ai", "open-source", "ai-models", "evaluation-framework", "provider-agnostic", "mlops", "benchmarking", "managed-by-terraform"]
  • mediumreadme#2
    Add a 'Why Openbench?' or 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    ## Why Openbench?

Openbench stands out with its truly provider-agnostic approach, supporting 30+ model providers and offering 95+ benchmarks for standardized, reproducible LLM evaluation, making it a robust alternative to other tools.
  • lowreadme#3
    Add a direct link to the homepage in the README intro

    Why:

    COPY-PASTE FIX
    For comprehensive documentation and more details, visit our official website at [openbench.dev](https://openbench.dev).

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 groq/openbench
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
langchain-ai/langchain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. langchain-ai/langchain · recommended 2×
  2. EleutherAI/lm-evaluation-harness · recommended 1×
  3. huggingface/evaluate · recommended 1×
  4. openai/evals · recommended 1×
  5. google/BIG-bench · recommended 1×
  • CATEGORY QUERY
    How can I benchmark different large language models reproducibly across various tasks?
    you: not recommended
    AI recommended (in order):
    1. EleutherAI's LM Evaluation Harness (lm-eval) (EleutherAI/lm-evaluation-harness)
    2. Hugging Face Evaluate Library (huggingface/evaluate)
    3. OpenAI Evals (openai/evals)
    4. LangChain Evaluation (LangChain.evaluate) (langchain-ai/langchain)
    5. DeepMind's Big-Bench (Beyond the Imitation Game Benchmark) (google/BIG-bench)
    6. MLflow (mlflow/mlflow)
    7. Weights & Biases (W&B) Prompts (wandb/wandb)

    AI recommended 7 alternatives but never named groq/openbench. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What open-source tools exist for evaluating LLM performance from multiple providers?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. Ragas (explodinggradients/ragas)
    3. DeepEval (confident-ai/deepeval)
    4. LLM Foundry (mosaicml/llm-foundry)
    5. Open-LLM-Leaderboard (huggingface/open_llm_leaderboard)
    6. LiteLLM (BerriAI/litellm)

    AI recommended 6 alternatives but never named groq/openbench. 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 groq/openbench?
    pass
    AI named groq/openbench explicitly

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

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