REPOGEO REPORT · LITE

PINTO0309/Tensorflow-bin

Default branch main · commit 98a47aed · scanned 6/5/2026, 8:12:02 AM

GitHub: 507 stars · 110 forks

AI VISIBILITY SCORE

40 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

2 pass · 0 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 PINTO0309/Tensorflow-bin, 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

Reposition the README H1 and opening paragraph to specify category

Why:

CURRENT

# Tensorflow-bin

**Older versions of Wheel files can be obtained from the [Previous version download script (GoogleDrive)](previous_versions).**

Prebuilt binary with Tensorflow Lite enabled. For RaspberryPi.

COPY-PASTE FIX

# Tensorflow-bin: Optimized Prebuilt TensorFlow Lite Wheels for ARM Single-Board Computers

This repository offers highly optimized, prebuilt TensorFlow Lite Python wheel packages for ARM-based single-board computers (e.g., Raspberry Pi, Jetson Nano). It features enhanced performance with XNNPACK (including multi-threading), FlexDelegate, and support for custom operations in MediaPipe, enabling efficient AI inference on edge devices.

mediumtopics#2

Enhance topics with more specific keywords

Why:

CURRENT

aarch64, armhf, armv7l, armv8, debian, pip, python, raspberrypi, raspbian, tensorflow, tensorflowlite, tflite, wheel

COPY-PASTE FIX

aarch64, armhf, armv7l, armv8, debian, pip, python, raspberrypi, raspbian, tensorflow, tensorflowlite, tflite, wheel, prebuilt-binaries, optimized-inference, single-board-computer, edge-ai, mediapipe-custom-ops, xnnpack, flexdelegate

lowreadme#3

Clarify relationship with TensorflowLite-bin in README

Why:

CURRENT

Minimal configuration stand-alone installer for Tensorflow Lite.
**https://github.com/PINTO0309/TensorflowLite-bin.git**

COPY-PASTE FIX

Add a section like:

## Related Projects

This repository, `Tensorflow-bin`, focuses on providing prebuilt, optimized TensorFlow Lite Python wheel packages. For a minimal configuration stand-alone installer for TensorFlow Lite, please refer to the companion project: [PINTO0309/TensorflowLite-bin](https://github.com/PINTO0309/TensorflowLite-bin.git).

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 PINTO0309/Tensorflow-bin

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

TensorFlow Lite

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

TensorFlow Lite · recommended 2×
PyTorch Mobile · recommended 2×
OpenVINO Toolkit · recommended 1×
ONNX Runtime · recommended 1×
TorchScript · recommended 1×

CATEGORY QUERY
Need prebuilt, optimized deep learning inference libraries for Raspberry Pi 64-bit.
you: not recommended
AI recommended (in order):
1. TensorFlow Lite
2. OpenVINO Toolkit
3. ONNX Runtime
4. PyTorch Mobile
5. TorchScript
6. NCNN
AI recommended 6 alternatives but never named PINTO0309/Tensorflow-bin. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Where to find Python wheel packages for accelerated AI inference on ARM single-board computers?
you: not recommended
AI recommended (in order):
1. TensorFlow Lite
2. PyTorch Mobile
3. NVIDIA Jetson
4. JetPack
5. Raspberry Pi OS
6. Coral
7. Qengineering
8. OpenVINO
AI recommended 8 alternatives but never named PINTO0309/Tensorflow-bin. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
pass
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 PINTO0309/Tensorflow-bin?
pass
AI named PINTO0309/Tensorflow-bin explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts PINTO0309/Tensorflow-bin in production, what risks or prerequisites should they evaluate first?
pass
AI named PINTO0309/Tensorflow-bin 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 PINTO0309/Tensorflow-bin solve, and who is the primary audience?
pass
AI named PINTO0309/Tensorflow-bin 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 PINTO0309/Tensorflow-bin. 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/PINTO0309/Tensorflow-bin.svg)](https://repogeo.com/en/r/PINTO0309/Tensorflow-bin)

HTML

<a href="https://repogeo.com/en/r/PINTO0309/Tensorflow-bin"><img src="https://repogeo.com/badge/PINTO0309/Tensorflow-bin.svg" alt="RepoGEO" /></a>

Pro

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PINTO0309/Tensorflow-bin — 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