RRepoGEO

REPOGEO REPORT · LITE

LLMServe/DistServe

Default branch main · commit 82831f16 · scanned 6/16/2026, 1:57:40 AM

GitHub: 820 stars · 95 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 LLMServe/DistServe, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Explicitly state 'distributed serving system' in the README's first sentence

    Why:

    CURRENT
    DistServe improves the performance of large language models (LLMs) serving by disaggregating the prefill and decoding computation.
    COPY-PASTE FIX
    DistServe is a high-performance **distributed serving system** for Large Language Models (LLMs) that significantly improves inference performance by disaggregating prefill and decoding computation, enabling efficient **distributed LLM inference** across multiple GPUs and nodes.
  • mediumhomepage#2
    Add a homepage URL to the repository's 'About' section

    Why:

    COPY-PASTE FIX
    https://github.com/LLMServe/DistServe (or a dedicated project website if one exists)

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 LLMServe/DistServe
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
vLLM
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. vLLM · recommended 2×
  2. TGI (Text Generation Inference) · recommended 2×
  3. TensorRT-LLM · recommended 2×
  4. OpenVINO · recommended 2×
  5. DeepSpeed-MII · recommended 1×
  • CATEGORY QUERY
    How to improve large language model serving performance by separating prefill and decoding?
    you: not recommended
    AI recommended (in order):
    1. vLLM
    2. TGI (Text Generation Inference)
    3. TensorRT-LLM
    4. DeepSpeed-MII
    5. OpenVINO
    6. PyTorch
    7. TensorFlow
    8. transformers

    AI recommended 8 alternatives but never named LLMServe/DistServe. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best tools for efficient LLM inference with distributed parallelism and continuous batching?
    you: not recommended
    AI recommended (in order):
    1. vLLM
    2. TGI (Text Generation Inference)
    3. DeepSpeed-MII (Microsoft Inference Interface)
    4. TensorRT-LLM
    5. Ray Serve
    6. OpenVINO
    7. TorchServe

    AI recommended 7 alternatives but never named LLMServe/DistServe. 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 LLMServe/DistServe?
    pass
    AI named LLMServe/DistServe explicitly

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

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

Subscribe to Pro for deep diagnoses

LLMServe/DistServe — 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