🧠
Model

ncnn

by Tencent tencent/ncnn
Free2AITools Nexus Index
50.3
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 62
P: Popularity 74
R: Recency 78
Q: Quality 70
Tech Context
Vital Performance
Low FNI signal 50.3 FNI Score
Tiny - Params
- Context
0 Downloads
Restricted NOASSERTION License
Model Information Summary
Entity Passport
Registry ID tencent/ncnn
License NOASSERTION
Provider github
📜

Cite this model

Academic & Research Attribution

BibTeX
@misc{tencent_ncnn,
  author = {Tencent},
  title = {ncnn Model},
  year = {2017},
  howpublished = {\url{https://github.com/Tencent/ncnn}},
  note = {Accessed via Free2AITools.}
}
APA Style
Tencent. (2017). ncnn [Model]. Free2AITools. https://github.com/Tencent/ncnn

🔬Technical Deep Dive

Full Specifications [+]

Quick Commands

🐙 Git Clone
git clone https://github.com/Tencent/ncnn

⚖️ Free2AITools Nexus Index V2.0

Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 62
Popularity (P) 74
Recency (R) 78
Quality (Q) 70

💬 Index Insight

FNI V2.0 for ncnn: Authority (A:62), Popularity (P:74), Recency (R:78), Quality (Q:70). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

Open data Updated: Live data
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🚀 What's Next?

Technical Deep Dive

ncnn

ncnn

License Download Total Count codecov

ncnn is a high-performance neural network inference computing framework optimized for mobile platforms. ncnn is deeply considerate about deployment and uses on mobile phones from the beginning of design. ncnn does not have third-party dependencies. It is cross-platform and runs faster than all known open-source frameworks on mobile phone cpu. Developers can easily deploy deep learning algorithm models to the mobile platform by using efficient ncnn implementation, creating intelligent APPs, and bringing artificial intelligence to your fingertips. ncnn is currently being used in many Tencent applications, such as QQ, Qzone, WeChat, Pitu, and so on.

ncnn 是一个为手机端极致优化的高性能神经网络前向计算框架。 ncnn 从设计之初深刻考虑手机端的部署和使用。 无第三方依赖,跨平台,手机端 cpu 的速度快于目前所有已知的开源框架。 基于 ncnn,开发者能够将深度学习算法轻松移植到手机端高效执行, 开发出人工智能 APP,将 AI 带到你的指尖。 ncnn 目前已在腾讯多款应用中使用,如:QQ,Qzone,微信,天天 P 图等。


技术交流 QQ 群
637093648 (超多大佬)
答案:卷卷卷卷卷(已满)
Telegram Group

https://t.me/ncnnyes

Discord Channel

https://discord.gg/YRsxgmF

Pocky QQ 群(MLIR YES!)
677104663 (超多大佬)
答案:multi-level intermediate representation
他们都不知道 pnnx 有多好用群
818998520 (新群!)

Download & Build status

https://github.com/Tencent/ncnn/releases/latest

⚠️ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

View Original Source →

📝 Limitations & Considerations

  • Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • FNI scores are relative rankings and may change as new models are added.

Social Proof

GitHub Repository
23.2KStars
4.4KForks
🔄 Updated daily

Source summary: Based on GitHub metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹ️ Verify with original source

🛡️ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
gh-model--tencent--ncnn
slug
tencent--ncnn
source
github
author
Tencent
license
NOASSERTION
tags
inference, high-preformance, simd, arm-neon, deep-learning, artificial-intelligence, android, ios, ncnn, vulkan, neural-network, caffe, mxnet, pytorch, onnx, darknet, tensorflow, mlir, keras, riscv, c++

⚙️ Technical Specs

pipeline tag
other

📊 Engagement & Metrics

downloads
0
stars
23,179
forks
4,419

Data indexed from public sources. Updated daily.

Metadata CoverageWe index Quick Start, Datasets Used, and Benchmarks via upstream pipelines. Sections are hidden when empty for this entity -- not all source providers expose every field.