RRepoGEO

REPOGEO REPORT · LITE

ray-project/ray-llm

Default branch master · commit 3f8f4da8 · scanned 6/26/2026, 7:22:02 PM

GitHub: 1,263 stars · 91 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)

3 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 ray-project/ray-llm, 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
  • highabout#1
    Clarify archived status and redirect in About description

    Why:

    CURRENT
    RayLLM - LLMs on Ray (Archived). Read README for more info.
    COPY-PASTE FIX
    ARCHIVED: RayLLM APIs are now integrated into Ray Serve and Ray Data. See https://docs.ray.io/en/latest/ray-llm/ for current LLM deployment on Ray.
  • highreadme#2
    Add license clarification to README

    Why:

    COPY-PASTE FIX
    Please note: This archived project does not have an explicit LICENSE file. For licensing information, refer to the main Ray project's Apache-2.0 License, as this project's functionality has been upstreamed there.
  • mediumtopics#3
    Update topics to reflect archived status and successor

    Why:

    CURRENT
    llm, llm-serving, ray
    COPY-PASTE FIX
    llm, llm-serving, ray, archived, deprecated, ray-serve

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 ray-project/ray-llm
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
TGI (Text Generation Inference)
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. TGI (Text Generation Inference) · recommended 2×
  2. Ray Serve · recommended 2×
  3. vLLM · recommended 1×
  4. NVIDIA Triton Inference Server · recommended 1×
  5. TensorRT-LLM · recommended 1×
  • CATEGORY QUERY
    What are the best frameworks for serving large language models with high throughput?
    you: not recommended
    AI recommended (in order):
    1. vLLM
    2. TGI (Text Generation Inference)
    3. NVIDIA Triton Inference Server
    4. TensorRT-LLM
    5. Ray Serve
    6. OpenVINO (Intel)

    AI recommended 6 alternatives but never named ray-project/ray-llm. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I easily deploy and scale multiple LLMs on a distributed cluster?
    you: not recommended
    AI recommended (in order):
    1. Ray Serve
    2. KServe
    3. Triton Inference Server
    4. TorchServe
    5. Hugging Face Inference Endpoints
    6. TGI (Text Generation Inference)
    7. Kubeflow

    AI recommended 7 alternatives but never named ray-project/ray-llm. 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 ray-project/ray-llm?
    pass
    AI named ray-project/ray-llm explicitly

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

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

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

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MARKDOWN (README)
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ray-project/ray-llm — 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