RRepoGEO

REPOGEO REPORT · LITE

NousResearch/DisTrO

Default branch main · commit 24f10628 · scanned 5/24/2026, 9:12:41 AM

GitHub: 1,031 stars · 53 forks

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 NousResearch/DisTrO, 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 relevant topics to the repository

    Why:

    COPY-PASTE FIX
    distributed-training, llm-training, gpu-optimization, communication-overhead, deep-learning, optimizers
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Choose and add a standard open-source license file (e.g., MIT, Apache-2.0) to the repository root.
  • mediumhomepage#3
    Set the repository homepage URL

    Why:

    COPY-PASTE FIX
    Set the homepage URL to a relevant project page or documentation site (e.g., a dedicated DisTrO project page, NousResearch's main site, or a documentation link).

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 NousResearch/DisTrO
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
DeepSpeed
Recommended in 4 of 2 queries
COMPETITOR LEADERBOARD
  1. DeepSpeed · recommended 4×
  2. PyTorch FSDP · recommended 3×
  3. Megatron-LM · recommended 2×
  4. NVIDIA NCCL · recommended 1×
  5. Intel oneCCL · recommended 1×
  • CATEGORY QUERY
    How to reduce GPU communication overhead for large-scale distributed model training?
    you: not recommended
    AI recommended (in order):
    1. NVIDIA NCCL
    2. Intel oneCCL
    3. Open MPI
    4. MPICH
    5. DeepSpeed
    6. Horovod
    7. PyTorch FSDP
    8. Slurm Workload Manager
    9. Kubernetes
    10. NVIDIA Device Plugin
    11. PyTorch DDP
    12. TensorFlow Distributed Strategy
    13. MirroredStrategy
    14. MultiWorkerMirroredStrategy
    15. DeepSpeed
    16. Megatron-LM
    17. PyTorch FSDP
    18. DeepSpeed

    AI recommended 18 alternatives but never named NousResearch/DisTrO. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for solutions to train large language models efficiently across multiple internet-connected GPUs.
    you: not recommended
    AI recommended (in order):
    1. PyTorch FSDP
    2. DeepSpeed
    3. Megatron-LM
    4. Hugging Face Accelerate
    5. Ray Train
    6. Colossal-AI

    AI recommended 6 alternatives but never named NousResearch/DisTrO. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    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 NousResearch/DisTrO?
    pass
    AI named NousResearch/DisTrO explicitly

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

  • If a team adopts NousResearch/DisTrO in production, what risks or prerequisites should they evaluate first?
    pass
    AI named NousResearch/DisTrO 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 NousResearch/DisTrO solve, and who is the primary audience?
    pass
    AI named NousResearch/DisTrO 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 NousResearch/DisTrO. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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NousResearch/DisTrO — 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
NousResearch/DisTrO — RepoGEO report