RRepoGEO

REPOGEO REPORT · LITE

alibaba/Pai-Megatron-Patch

Default branch main · commit a098ca5a · scanned 5/23/2026, 10:21:57 AM

GitHub: 1,575 stars · 228 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 alibaba/Pai-Megatron-Patch, 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 the repository

    Why:

    COPY-PASTE FIX
    ["LLM", "VLM", "Large Scale Training", "Megatron-LM", "Deep Learning", "Alibaba Cloud", "PAI", "AI Training", "Distributed Training", "Model Training"]
  • highreadme#2
    Reposition the README introduction to highlight unique value

    Why:

    CURRENT
    Pai-Megatron-Patch (https://github.com/alibaba/Pai-Megatron-Patch) is a deep learning training toolkit built for developers to train and predict LLMs & VLMs by using Megatron framework easily.
    COPY-PASTE FIX
    Pai-Megatron-Patch is an optimized deep learning training toolkit for developers to efficiently train and predict large language (LLMs) and vision (VLMs) models using the Megatron-LM framework, specifically tailored for Alibaba Cloud's PAI platform.
  • mediumcomparison#3
    Add a comparison section to the README

    Why:

    COPY-PASTE FIX
    Add a new section titled 'Comparison with Megatron-LM and other frameworks' to the README, detailing how Pai-Megatron-Patch optimizes training for LLMs/VLMs, especially on Alibaba Cloud PAI, compared to vanilla Megatron-LM, Transformers, or DeepSpeed.

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 alibaba/Pai-Megatron-Patch
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Megatron-LM
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Megatron-LM · recommended 2×
  2. NVIDIA DGX Systems · recommended 1×
  3. AWS EC2 P4d/P5 Instances · recommended 1×
  4. Google Cloud TPU Pods · recommended 1×
  5. Microsoft Azure ND H100 v5 / ND A100 v4 Instances · recommended 1×
  • CATEGORY QUERY
    How to efficiently train large language and vision models at scale?
    you: not recommended
    AI recommended (in order):
    1. NVIDIA DGX Systems
    2. AWS EC2 P4d/P5 Instances
    3. Google Cloud TPU Pods
    4. Microsoft Azure ND H100 v5 / ND A100 v4 Instances
    5. PyTorch FSDP
    6. DeepSpeed
    7. Megatron-LM

    AI recommended 7 alternatives but never named alibaba/Pai-Megatron-Patch. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are efficient alternatives to Transformers or DeepSpeed for large model training?
    you: not recommended
    AI recommended (in order):
    1. Megatron-LM
    2. FairScale
    3. Colossal-AI
    4. Accelerate
    5. JAX/Flax
    6. PaddlePaddle (Fleet API)

    AI recommended 6 alternatives but never named alibaba/Pai-Megatron-Patch. 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 alibaba/Pai-Megatron-Patch?
    pass
    AI named alibaba/Pai-Megatron-Patch explicitly

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

  • If a team adopts alibaba/Pai-Megatron-Patch in production, what risks or prerequisites should they evaluate first?
    pass
    AI named alibaba/Pai-Megatron-Patch 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 alibaba/Pai-Megatron-Patch solve, and who is the primary audience?
    pass
    AI named alibaba/Pai-Megatron-Patch 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 alibaba/Pai-Megatron-Patch. 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/alibaba/Pai-Megatron-Patch.svg)](https://repogeo.com/en/r/alibaba/Pai-Megatron-Patch)
HTML
<a href="https://repogeo.com/en/r/alibaba/Pai-Megatron-Patch"><img src="https://repogeo.com/badge/alibaba/Pai-Megatron-Patch.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

alibaba/Pai-Megatron-Patch — 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