RRepoGEO

REPOGEO REPORT · LITE

volcengine/veScale

Default branch main · commit 20cf5c71 · scanned 5/16/2026, 9:02:30 PM

GitHub: 1,009 stars · 61 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 volcengine/veScale, 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
  • highreadme#1
    Strengthen README's opening to clearly position veScale as a distributed training library

    Why:

    CURRENT
    # Old veScale Has been Moved to `legacy/`; New veScale is Coming ...

<div align="center">
    
</div>

# veScale

veScale is an internal PyTorch Distributed library, enabling hyperscale distributed training of LLMs and RLs. This repo open-sources a small piece of veScale for a better community.
    COPY-PASTE FIX
    # veScale: A PyTorch Distributed Library for Hyperscale LLM and RL Training

veScale is a powerful PyTorch Distributed library designed to enable hyperscale distributed training of Large Language Models (LLMs) and Reinforcement Learning (RL) models. This repository provides robust, open-source components of veScale, offering efficient and scalable deep learning solutions.
  • mediumhomepage#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://github.com/volcengine/veScale
  • lowtopics#3
    Expand repository topics to include distributed training specifics

    Why:

    CURRENT
    llm-training, pytorch
    COPY-PASTE FIX
    llm-training, pytorch, distributed-training, fsdp

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 volcengine/veScale
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PyTorch FSDP
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. PyTorch FSDP · recommended 2×
  2. DeepSpeed · recommended 2×
  3. Megatron-LM · recommended 2×
  4. Accelerate · recommended 1×
  5. Colossal-AI · recommended 1×
  • CATEGORY QUERY
    How to efficiently scale PyTorch distributed training for large language models?
    you: not recommended
    AI recommended (in order):
    1. PyTorch FSDP
    2. DeepSpeed
    3. Megatron-LM
    4. Accelerate
    5. Colossal-AI
    6. FairScale

    AI recommended 6 alternatives but never named volcengine/veScale. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best PyTorch libraries for distributed training of very large models?
    you: not recommended
    AI recommended (in order):
    1. PyTorch FSDP
    2. DeepSpeed
    3. Hugging Face Accelerate
    4. PyTorch DDP
    5. Megatron-LM

    AI recommended 5 alternatives but never named volcengine/veScale. 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 volcengine/veScale?
    pass
    AI named volcengine/veScale explicitly

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

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

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

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volcengine/veScale — 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