RRepoGEO

REPOGEO REPORT · LITE

Jittor/JittorLLMs

Default branch main · commit 8f2d3ce5 · scanned 5/17/2026, 3:08:52 PM

GitHub: 2,422 stars · 187 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)

2 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 Jittor/JittorLLMs, 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 topics to the repository

    Why:

    COPY-PASTE FIX
    llm, large-language-models, inference, cpu-inference, low-resource, portable, jittor, deep-learning, nlp, chatglm, llama, pangualpha, chatrwkv
  • highreadme#2
    Strengthen the README's opening statement to clarify its core purpose

    Why:

    CURRENT
    # 计图大模型推理库 - 笔记本没有显卡也能跑大模型
本大模型推理库JittorLLMs有以下几个特点：
    COPY-PASTE FIX
    # JittorLLMs: 高性能、低成本大模型推理库 - 笔记本没有显卡也能跑大模型
JittorLLMs 是一个基于 Jittor 框架的高性能、低成本大模型推理库，专为在普通机器上（包括无显卡、低内存环境）实现大模型本地部署而设计，提供与 llama.cpp、Ollama 等工具类似的轻量级、可移植的 LLM 运行体验。本库具有以下几个特点：
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://jittor.org/jittorllms

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 Jittor/JittorLLMs
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
llama.cpp
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. llama.cpp · recommended 2×
  2. Ollama · recommended 2×
  3. Intel OpenVINO · recommended 2×
  4. ONNX Runtime · recommended 2×
  5. Transformers.js · recommended 1×
  • CATEGORY QUERY
    Looking for an LLM inference solution that runs on CPU with low RAM footprint.
    you: not recommended
    AI recommended (in order):
    1. llama.cpp
    2. Ollama
    3. Transformers.js
    4. ONNX Runtime Web
    5. Intel OpenVINO
    6. ONNX Runtime

    AI recommended 6 alternatives but never named Jittor/JittorLLMs. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best options for fast and portable LLM inference on standard machines?
    you: not recommended
    AI recommended (in order):
    1. llama.cpp
    2. Ollama
    3. MLC LLM
    4. ONNX Runtime
    5. Intel OpenVINO
    6. TensorRT-LLM

    AI recommended 6 alternatives but never named Jittor/JittorLLMs. 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 Jittor/JittorLLMs?
    pass
    AI named Jittor/JittorLLMs explicitly

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

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

Subscribe to Pro for deep diagnoses

Jittor/JittorLLMs — 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