RRepoGEO

REPOGEO REPORT · LITE

gonka-ai/gonka

Default branch main · commit d5e30ca8 · scanned 6/3/2026, 9:02:01 AM

GitHub: 516 stars · 107 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 gonka-ai/gonka, 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
    Update the repository's "About" description

    Why:

    CURRENT
    Gonka AI Compute
    COPY-PASTE FIX
    Decentralized AI infrastructure for model training and inference, offering an alternative to centralized cloud providers.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    decentralized-ai, ai-infrastructure, llm-training, distributed-compute, blockchain, proof-of-work, machine-learning, inference, gpu-compute
  • mediumreadme#3
    Clarify the project's license in the README

    Why:

    COPY-PASTE FIX
    Add a "## License" section to the README stating: "This project operates under a custom license. Please refer to the [LICENSE](LICENSE) file in the repository for the full terms and conditions."

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 gonka-ai/gonka
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 3 of 2 queries
COMPETITOR LEADERBOARD
  1. ray-project/ray · recommended 3×
  2. akash-network/node · recommended 1×
  3. render-network/render-network · recommended 1×
  4. Vast.ai · recommended 1×
  5. golemfactory/golem · recommended 1×
  • CATEGORY QUERY
    How to find affordable decentralized compute for large language model training?
    you: not recommended
    AI recommended (in order):
    1. Akash Network (akash-network/node)
    2. Render Network (render-network/render-network)
    3. Vast.ai
    4. Golem Network (golemfactory/golem)
    5. Flux (RunOnFlux/flux)
    6. io.net (ionet-cloud/io.net)

    AI recommended 6 alternatives but never named gonka-ai/gonka. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a distributed platform to run transformer-based AI model inference and training.
    you: not recommended
    AI recommended (in order):
    1. PyTorch Lightning (Lightning-AI/lightning)
    2. PyTorch Distributed (pytorch/pytorch)
    3. Hugging Face Accelerate (huggingface/accelerate)
    4. DeepSpeed (microsoft/DeepSpeed)
    5. Ray (ray-project/ray)
    6. Ray Train (ray-project/ray)
    7. Ray Core (ray-project/ray)
    8. TensorFlow (tensorflow/tensorflow)
    9. Keras (keras-team/keras)
    10. NVIDIA Triton Inference Server (triton-inference-server/server)
    11. Open MPI (open-mpi/ompi)
    12. Horovod (horovod/horovod)

    AI recommended 12 alternatives but never named gonka-ai/gonka. 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 gonka-ai/gonka?
    pass
    AI named gonka-ai/gonka explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of gonka-ai/gonka. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/gonka-ai/gonka.svg)](https://repogeo.com/en/r/gonka-ai/gonka)
HTML
<a href="https://repogeo.com/en/r/gonka-ai/gonka"><img src="https://repogeo.com/badge/gonka-ai/gonka.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

gonka-ai/gonka — 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