RRepoGEO

REPOGEO REPORT · LITE

PrimeIntellect-ai/prime-rl

Default branch main · commit b2ba40b5 · scanned 5/14/2026, 1:57:34 PM

GitHub: 1,368 stars · 288 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 PrimeIntellect-ai/prime-rl, 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 topics to the repository

    Why:

    COPY-PASTE FIX
    reinforcement-learning, distributed-training, multi-gpu, agentic-ai, llm-training, pytorch, slurm, kubernetes, multimodal, asynchronous-rl, large-scale-ai
  • highreadme#2
    Strengthen the README's opening paragraph to emphasize core differentiators

    Why:

    CURRENT
    PRIME-RL is a framework for large-scale reinforcement learning. It is designed to be easy to use and hackable, yet capable of scaling to 1000+ GPUs.
    COPY-PASTE FIX
    PRIME-RL is a high-performance framework for large-scale, asynchronous, and agentic reinforcement learning, designed to scale efficiently across 1000+ GPUs for training complex models like 1T+ MoE with FSDP2 and vLLM.
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://primeintellect.ai/prime-rl (or relevant project/organization URL)

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 PrimeIntellect-ai/prime-rl
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Ray RLlib
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Ray RLlib · recommended 2×
  2. Acme · recommended 2×
  3. OpenSpiel · recommended 2×
  4. PyTorch Distributed (DDP/FSDP) · recommended 1×
  5. TensorFlow Reverb · recommended 1×
  • CATEGORY QUERY
    How can I efficiently train large-scale agentic reinforcement learning models asynchronously across many GPUs?
    you: not recommended
    AI recommended (in order):
    1. Ray RLlib
    2. Acme
    3. OpenSpiel
    4. PyTorch Distributed (DDP/FSDP)
    5. TensorFlow Reverb
    6. TF-Agents
    7. Catalyst

    AI recommended 7 alternatives but never named PrimeIntellect-ai/prime-rl. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What frameworks support distributed reinforcement learning training for multimodal models on Kubernetes clusters?
    you: not recommended
    AI recommended (in order):
    1. Ray RLlib
    2. Ray
    3. KubeRay operator
    4. OpenSpiel
    5. Kubeflow Pipelines
    6. Argo Workflows
    7. PyTorch Lightning
    8. TensorFlow
    9. Acme
    10. Launchpad
    11. PyTorchJob
    12. TFJob
    13. TorchRL
    14. TensorFlow Agents (TF-Agents)

    AI recommended 14 alternatives but never named PrimeIntellect-ai/prime-rl. 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 PrimeIntellect-ai/prime-rl?
    pass
    AI named PrimeIntellect-ai/prime-rl explicitly

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

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

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

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PrimeIntellect-ai/prime-rl — 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