RRepoGEO

REPOGEO REPORT · LITE

tjake/Jlama

Default branch main · commit 7b8ba424 · scanned 5/27/2026, 12:12:11 AM

GitHub: 1,287 stars · 157 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 tjake/Jlama, 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
    Add a clear differentiator statement to the README's opening

    Why:

    CURRENT
    The README starts with '# 🦙 Jlama: A modern LLM inference engine for Java' followed by badges and features.
    COPY-PASTE FIX
    Add the following sentence immediately after the H1: "Unlike most LLM inference solutions, Jlama is a pure Java implementation designed for local execution, requiring no native dependencies."
  • mediumreadme#2
    Enhance 'What is it used for?' section to highlight unique benefits

    Why:

    CURRENT
    Add LLM Inference directly to your Java application. To learn more read the DeepWiki docs.
    COPY-PASTE FIX
    Jlama allows you to embed performant LLM inference directly into your Java applications, leveraging pure Java for local execution without external native dependencies. This is ideal for scenarios requiring on-device inference, privacy, or custom integration within the JVM ecosystem.
  • lowhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    Set the homepage URL to https://deepwiki.com/tjake/Jlama

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 tjake/Jlama
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI API
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI API · recommended 1×
  2. openai-java · recommended 1×
  3. Google Cloud Vertex AI · recommended 1×
  4. google-cloud-vertexai · recommended 1×
  5. Hugging Face Inference API · recommended 1×
  • CATEGORY QUERY
    How can I integrate large language model inference capabilities into my Java application?
    you: not recommended
    AI recommended (in order):
    1. OpenAI API
    2. openai-java
    3. Google Cloud Vertex AI
    4. google-cloud-vertexai
    5. Hugging Face Inference API
    6. OkHttp
    7. Apache HttpClient
    8. LangChain4j
    9. llama.cpp
    10. Microsoft Azure OpenAI Service
    11. azure-ai-openai

    AI recommended 11 alternatives but never named tjake/Jlama. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a performant Java library to run quantized transformer models locally with SIMD acceleration.
    you: not recommended
    AI recommended (in order):
    1. ONNX Runtime (microsoft/onnxruntime)
    2. Deeplearning4j (deeplearning4j/deeplearning4j)
    3. TensorFlow Lite (tensorflow/tensorflow)
    4. OpenVINO Toolkit (openvinotoolkit/openvino)
    5. Apache MXNet (apache/mxnet)
    6. PyTorch (pytorch/pytorch)

    AI recommended 6 alternatives but never named tjake/Jlama. 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 tjake/Jlama?
    pass
    AI named tjake/Jlama explicitly

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

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

Subscribe to Pro for deep diagnoses

tjake/Jlama — 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