RRepoGEO

REPOGEO REPORT · LITE

airockchip/rknn-llm

Default branch main · commit f7df8e5d · scanned 5/13/2026, 6:02:20 PM

GitHub: 1,449 stars · 193 forks

AI VISIBILITY SCORE
17 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
1 / 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 airockchip/rknn-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

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

OVERALL DIRECTION
  • highabout#1
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    RKLLM software stack for deploying and optimizing large language models (LLMs) on Rockchip NPU platforms, including RK3588, RK3576, RK3562, and RV1126B series. Provides RKLLM-Toolkit for model conversion and RKLLM Runtime C/C++ API for efficient inference on edge AI devices.
  • mediumreadme#2
    Clarify the existing license(s) in the README

    Why:

    COPY-PASTE FIX
    Add a section to the README, perhaps titled 'License,' stating: 'This project includes a LICENSE file. Please refer to this file for the specific terms and conditions governing the use and distribution of this software. It is a custom license designed for Rockchip projects.'

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 airockchip/rknn-llm
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ONNX Runtime
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ONNX Runtime · recommended 2×
  2. TensorFlow Lite · recommended 2×
  3. OpenVINO Toolkit · recommended 2×
  4. Qualcomm AI Engine Direct (QNN SDK) · recommended 1×
  5. Arm NN · recommended 1×
  • CATEGORY QUERY
    Looking for a toolkit to deploy and optimize large language models on ARM NPU devices.
    you: not recommended
    AI recommended (in order):
    1. Qualcomm AI Engine Direct (QNN SDK)
    2. Arm NN
    3. ONNX Runtime
    4. TensorFlow Lite
    5. MediaTek NeuroPilot SDK
    6. NVIDIA JetPack SDK
    7. OpenVINO Toolkit

    AI recommended 7 alternatives but never named airockchip/rknn-llm. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What C/C++ API can I use to accelerate large language model inference on embedded AI chips?
    you: not recommended
    AI recommended (in order):
    1. ONNX Runtime
    2. TensorFlow Lite
    3. PyTorch Mobile
    4. OpenVINO Toolkit
    5. TensorRT
    6. ARM NN
    7. TVM

    AI recommended 7 alternatives but never named airockchip/rknn-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
    fail

    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 airockchip/rknn-llm?
    pass
    AI did not name airockchip/rknn-llm — likely talking about a different project

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

  • If a team adopts airockchip/rknn-llm in production, what risks or prerequisites should they evaluate first?
    pass
    AI named airockchip/rknn-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 airockchip/rknn-llm solve, and who is the primary audience?
    pass
    AI did not name airockchip/rknn-llm — likely talking about a different project

    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 airockchip/rknn-llm. 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/airockchip/rknn-llm.svg)](https://repogeo.com/en/r/airockchip/rknn-llm)
HTML
<a href="https://repogeo.com/en/r/airockchip/rknn-llm"><img src="https://repogeo.com/badge/airockchip/rknn-llm.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

airockchip/rknn-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