AI · alternatives · 2026

24 alternatives to Light-weight C++ library for Keras

This is a bunch of code to port Keras neural network model into pure C++. - pplonski/keras2cpp

This is a lightweight C++ library that enables developers to run Keras models in C++ applications. It allows machine learning models trained in Keras to be deployed and executed efficiently in C++ environments without… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Light-weight C++ library for Keras launched in 2017; newer entries below may have overtaken it.

1
TensorFlow 1.0▲823
Open-source machine learning library by Google
2017 · tensorflow.org · its alternatives →
2
I built a tensor library from scratch in C++/CUDA▲119
Hi HN, Over the past few months, I've been building `dsc`, a tensor library from scratch in C++/CUDA. My main focus has been on getting the basics right, prioritizing a clean API, simplicity, and clear observability for running small LLMs locally. The key features are: - C++ core with CUDA support written from scratch. - A familiar, PyTorch-like Python API. - Runs real models: it's complete enough to load a model like Qwen from HuggingFace and run inference on both CUDA and CPU with a single line change[1]. - Simple, built-in observability for both Python and C++. Next on the roadmap is…
2025 · github.com · its alternatives →
3
Port of OpenAI's Whisper model in C/C++▲399
Hi HN, OpenAI recently released a model for automatic speech recognition called Whisper [0]. I decided to reimplement the inference of the model from scratch using C/C++. To achieve this I implemented a minimalistic tensor library in C and ported the high-level architecture of the model in C++. The entire code is less than 8000 lines of code and is contained in just 2 source files without any third-party dependencies. The Github project is here: https://github.com/ggerganov/whisper.cpp With this implementation I can very easily build and run the model - “make…
2022 · github.com · its alternatives →
4
Set of trained deep learning models for computer vision▲127
Keras code and weights files for popular deep learning models. - fchollet/deep-learning-models
2016 · github.com · its alternatives →
5
Thinc, a new deep learning library by the makers of spaCy and FastAPI▲250
Thinc is a lightweight type-checked deep learning library for composing models, with support for layers defined in frameworks like PyTorch and TensorFlow.
2020 · thinc.ai · its alternatives →
6
Compile ML models into dependency-free source code for easy deployment▲37
I'm a machine learning engineer who always found it annoying to integrate ML models into phone apps, smartwatch apps, microcontroller firmware etc... Why do we need all these libraries and runtimes with all the overhead, compatibility issues and other headaches, when it's just some math to be executed? So I made a compiler that simply converts the model into plain source code with no dependencies, and it actually solved all my deployment problems. Now I'm curious if it can help anyone else too. Through the link you can submit your model file (Keras h5, onnx soon to be supported), and I'll…
2023 · waveworks.dk · its alternatives →
7
Spektral – Deep learning on graphs with Keras▲67
Graph Neural Networks with Keras and Tensorflow 2. - danielegrattarola/spektral
2019 · github.com · its alternatives →
8
Weights & Biases▲110
Developer tools for deep learning & machine learning
2019 · wandb.ai · its alternatives →
9
Richard – A CNN written in C++ and Vulkan (no ML or math libs)▲184
This started out as a personal effort to learn more about machine learning. It's currently a CLI app where you give it a JSON file specifying your network architecture and hyperparameters and point it to your training data, then invoke it again in 'eval' mode with some data it's not seen before and it will try to classify each sample. I don't see many other people using Vulkan for GPGPU, and there may be many good reasons for that, but I wanted to try something a bit different. I've made every attempt to make the code very clean and readable and I've written up the math in…
2024 · github.com · its alternatives →
10
Run TRELLIS.2 Image-to-3D generation natively on Apple Silicon▲202
I ported Microsoft's TRELLIS.2 (4B parameter image-to-3D model) to run on Apple Silicon via PyTorch MPS. The original requires CUDA with flash_attn, nvdiffrast, and custom sparse convolution kernels: none of which work on Mac. I replaced the CUDA-specific ops with pure-PyTorch alternatives: a gather-scatter sparse 3D convolution, SDPA attention for sparse transformers, and a Python-based mesh extraction replacing CUDA hashmap operations. Total changes are a few hundred lines across 9 files. Generates ~400K vertex meshes from single photos in about 3.5 minutes on M4 Pro (24GB). Not as fast as…
Apr 2026 · github.com · its alternatives →
11
MakeML▲274
Train Neural Networks without a line of code
2019 · makeml.app · its alternatives →
12
Txeo – A Modern C++ Wrapper for TensorFlow▲52
Txeo is a lightweight and intuitive C++ wrapper for TensorFlow, designed to simplify TensorFlow C++ development while preserving high performance and flexibility. Built entirely with Modern C++, Txeo allows developers to use TensorFlow with the ease of a high-level API, eliminating the complexity of its low-level C++ interface.
2025 · github.com · its alternatives →
13N5
NN-512 – Generate standalone C code for neural nets▲111
2020 · nn-512.com · its alternatives →
14
Comgra: A library for debugging and understanding neural networks▲66
I'm a machine learning engineer and researcher. I got fed up with how difficult it is to understand why neural networks behave the way they do, so i wrote a library to help with it. Comgra (computation graph analysis) is a library you can use with pytorch to extract all the tensor data you care about and visualize it graphically in a browser. This allows for a much more detailed analysis of what is happening than the usual approach of using tensorboard. You can go investigate tensors as training proceeds, drill down into individual neurons, inspect single data sets that are of special…
2023 · github.com · its alternatives →
15HP
High-performance ahead-of-time compiler for Machine Learning▲83
2018 · scss.tcd.ie · its alternatives →
16
C++ virtual_vec vector implementation▲39
Contribute to kkuehlz/virtual_vec development by creating an account on GitHub.
2021 · github.com · its alternatives →
17
Dockerized GPU Deep Learning Solution (Code and Blog and TensorFlow Demo)▲80
An on-premises, bare-metal solution for deploying GPU-powered applications in containers - emergingstack/es-dev-stack
2016 · github.com · its alternatives →
18
KeraSH, a ML Framework in Shell▲15
World's leading ML framework in shell. Contribute to MightyGoldenOctopus/KeraSH development by creating an account on GitHub.
2019 · github.com · its alternatives →
19
TensorFlow 1.0▲80
Open-source machine learning library by Google
2018 · tensorflow.org · its alternatives →
20
Initial release of the distributed TensorFlow runtime▲85
An Open Source Machine Learning Framework for Everyone - tensorflow/tensorflow/core/distributed_runtime at master · tensorflow/tensorflow
2016 · github.com · its alternatives →
21
Layered – Neural Networks in Python 3▲56
Clean implementation of feed forward neural networks - danijar/layered
2015 · github.com · its alternatives →
22PO
PlaidML, open source deep learning for any GPU▲52
Our company Vertex.AI has been working on this for a while but this is the first public release. We're starting with using PlaidML to bring OpenCL support to Keras and more frameworks, platforms, etc are coming. Yes, this means you can use use your AMD GPU for deep learning dev. Sorry, no Mac or Windows support yet although the brave can try building from source (it should work). http://vertex.ai/blog/announcing-plaidml https://github.com/plaidml/plaidml
2017 · its alternatives →
23
A Fast, Malloc-Free C++14 Json Parser and Encoder▲98
Meta programming utilities for C++14. Merged in matt-42/lithium - matt-42/iod
2014 · github.com · its alternatives →
24
To better understand Neural Networks I built one from scratch in C++▲10
Trying to understand neural nets by building a simple one from scratch - kretash/BasicNeuralNet
2017 · github.com · its alternatives →

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