RRepoGEO

REPOGEO REPORT · LITE

Lightning-AI/lightning-thunder

Default branch main · commit 99850362 · scanned 5/27/2026, 6:06:47 AM

GitHub: 1,459 stars · 114 forks

AI VISIBILITY SCORE
22 /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
1 / 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 Lightning-AI/lightning-thunder, 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 improve categorization

    Why:

    COPY-PASTE FIX
    pytorch, compiler, deep-learning, machine-learning, optimization, performance, inference, training, ai, gpu
  • highreadme#2
    Reposition the README's main headline to clearly state its function

    Why:

    CURRENT
    # Give your PyTorch models superpowers ⚡
    COPY-PASTE FIX
    # Lightning Thunder: Source-to-Source PyTorch Compiler for Accelerated Training & Inference
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    [Insert official project homepage URL here, e.g., https://lightning.ai/thunder]

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 Lightning-AI/lightning-thunder
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
DeepSpeed
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. DeepSpeed · recommended 2×
  2. NVIDIA Apex · recommended 1×
  3. PyTorch torch.compile · recommended 1×
  4. ONNX Runtime · recommended 1×
  5. NVIDIA TensorRT · recommended 1×
  • CATEGORY QUERY
    How can I significantly speed up PyTorch model training and inference performance?
    you: not recommended
    AI recommended (in order):
    1. NVIDIA Apex
    2. PyTorch torch.compile
    3. ONNX Runtime
    4. NVIDIA TensorRT
    5. DDP
    6. FSDP
    7. Intel Extension for PyTorch
    8. DeepSpeed

    AI recommended 8 alternatives but never named Lightning-AI/lightning-thunder. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools provide advanced PyTorch optimization for memory, parallelism, and quantization?
    you: not recommended
    AI recommended (in order):
    1. DeepSpeed
    2. PyTorch FSDP
    3. Accelerate
    4. FairScale
    5. NVIDIA APEX
    6. PyTorch Quantization Toolkit

    AI recommended 6 alternatives but never named Lightning-AI/lightning-thunder. 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 Lightning-AI/lightning-thunder?
    pass
    AI did not name Lightning-AI/lightning-thunder — likely talking about a different project

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

  • If a team adopts Lightning-AI/lightning-thunder in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Lightning-AI/lightning-thunder 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 Lightning-AI/lightning-thunder solve, and who is the primary audience?
    pass
    AI did not name Lightning-AI/lightning-thunder — likely talking about a different project

    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 Lightning-AI/lightning-thunder. 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/Lightning-AI/lightning-thunder.svg)](https://repogeo.com/en/r/Lightning-AI/lightning-thunder)
HTML
<a href="https://repogeo.com/en/r/Lightning-AI/lightning-thunder"><img src="https://repogeo.com/badge/Lightning-AI/lightning-thunder.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

Lightning-AI/lightning-thunder — 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