REPOGEO REPORT · LITE

llumnix-project/llumnix-ray

Default branch main · commit 3fb6c037 · scanned 6/8/2026, 6:27:15 PM

GitHub: 551 stars · 50 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 llumnix-project/llumnix-ray, 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 GitHub topics

Why:

COPY-PASTE FIX

llm, llm-serving, ray, distributed-systems, inference, machine-learning, deep-learning, vllm, prototyping

highreadme#2

Add a clear, concise positioning statement for Llumnix-Ray (V0)

Why:

CURRENT

<p align="center">
| <a href="https://github.com/AlibabaPAI/llumnix/blob/main/docs"><b>Documentation</b></a> | <a href="https://arxiv.org/abs/2406.03243"><b>Paper</b></a> | <a href="https://llumnix.slack.com"><b>Developer Slack</b></a> |
</p>

COPY-PASTE FIX

<p align="center">This repository, Llumnix-Ray (V0), provides an efficient multi-instance LLM serving solution built on the Ray distributed computing framework, ideal for local deployments and rapid prototyping.</p>
<p align="center">
| <a href="https://github.com/AlibabaPAI/llumnix/blob/main/docs"><b>Documentation</b></a> | <a href="https://arxiv.org/abs/2406.03243"><b>Paper</b></a> | <a href="https://llumnix.slack.com"><b>Developer Slack</b></a> |
</p>

mediumhomepage#3
Add a homepage URL
Why:
COPY-PASTE FIX
```
https://github.com/AlibabaPAI/llumnix/blob/main/docs
```

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 llumnix-project/llumnix-ray

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

vLLM

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

vLLM · recommended 2×
Ollama · recommended 2×
LiteLLM · recommended 2×
TGI (Text Generation Inference) · recommended 1×
DeepSpeed-MII (Model Inference Interface) · recommended 1×

CATEGORY QUERY
How can I efficiently serve multiple large language models on a single machine?
you: not recommended
AI recommended (in order):
1. vLLM
2. TGI (Text Generation Inference)
3. DeepSpeed-MII (Model Inference Interface)
4. TensorRT-LLM
5. Ollama
6. LiteLLM
7. OpenLLM
AI recommended 7 alternatives but never named llumnix-project/llumnix-ray. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Which frameworks simplify local deployment and experimentation for multi-instance LLM serving?
you: not recommended
AI recommended (in order):
1. vLLM
2. TGI
3. LiteLLM
4. Hugging Face `transformers`
5. Ray Serve
6. Ollama
7. FastAPI
AI recommended 7 alternatives but never named llumnix-project/llumnix-ray. 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 llumnix-project/llumnix-ray?
pass
AI named llumnix-project/llumnix-ray explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts llumnix-project/llumnix-ray in production, what risks or prerequisites should they evaluate first?
pass
AI named llumnix-project/llumnix-ray 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 llumnix-project/llumnix-ray solve, and who is the primary audience?
pass
AI named llumnix-project/llumnix-ray 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 llumnix-project/llumnix-ray. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/llumnix-project/llumnix-ray.svg)](https://repogeo.com/en/r/llumnix-project/llumnix-ray)

HTML

<a href="https://repogeo.com/en/r/llumnix-project/llumnix-ray"><img src="https://repogeo.com/badge/llumnix-project/llumnix-ray.svg" alt="RepoGEO" /></a>

Pro

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llumnix-project/llumnix-ray — 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