AI · alternatives · 2026

24 alternatives to Neural Network Evolution Playground with Backprop NEAT

Neural Network Evolution Playground with Backprop NEAT uses a genetic algorithm to automatically design neural network structures for classifying datasets. It allows users to experiment with evolving atypical network… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 1 we have checked on their own sites, 1 of them free or with a free tier. Neural Network Evolution Playground with Backprop NEAT launched in 2016; newer entries below may have overtaken it.

1
Machine Learning Playground▲169
Breathtaking visuals for learning ML techniques.
2017 · ml-playground.com · its alternatives →
2
Netmind Power▲272
Hi HN, We just opened public access to Qwen3‑Coder‑480B‑A35B‑Instruct via a REST/SDK API. Why it might be interesting: - Fully open-source (Apache‑2.0): https://github.com/QwenLM/Qwen3-Coder - 480B params (35B active MoE), long context up to 1M tokens with YaRN - Matches Claude Sonnet/GPT‑4o on SWE-Bench Verified (81.6%) - Free tier: 100K tokens/month
2023 · netmind.ai · its alternatives →
3
I built a game to help you learn neural network architectures▲321
2024 · graphgame.sabrina.dev · its alternatives →
4
AI Playground by Vercel Labs▲249
Hey, Jared Palmer (creator of this playground) here. Really excited to ship this. I’ve been building this over the past few weeks to compare LLMs from different providers like OpenAI, Anthropic, Cohere, etc. At Vercel, I manage our Frameworks division (including Next.js, Svelte, and Turbo) and wanted to also dogfood some of the latest features in a slightly larger application. This playground takes a lot of inspiration from https://nat.dev and is built on Tailwind, ui.shadcn.com, and some upcoming Vercel products we’re announcing soon. We’re going to continue adding models to…
2023 · play.vercel.ai · its alternatives →
5
Boldly go where Gradient Descent has never gone before with DiscoGrad▲232
Trying to do gradient descent using automatic differentiation over branchy programs? Or to combine them with neural networks for end-to-end training? Then this might be interesting to you. We develped DiscoGrad, a tool for automatic differentiation through C++ programs involving input-dependent control flow (e.g., "if (f(x) < c) { ... }", differentiating wrt. x) and randomness. Our initial motivation was to enable the use of gradient descent with simulations, which often rely heavily on such discrete branching. The latter makes plain autodiff mostly useless, since it can only account for the…
2024 · github.com · its alternatives →
6
Recurrent neural net plays 'neural slime volleyball' in JavaScript▲147
2015 · otoro.net · its alternatives →
7
Watch a neural net learn to play Snake▲205
In browser PPO training demo, made possible by tinygrad: TinyJit -> WebGPU kernels. Requires WebGPU.
May 2026 · ppo.gradexp.xyz · its alternatives →
8IB
I built a toy TPU that can do inference and training on the XOR problem▲134
We wanted to do something very challenging to prove to ourselves that we can do anything we put our mind to. The reasoning for why we chose to build a toy TPU specifically is fairly simple: - Building a chip for ML workloads seemed cool - There was no well-documented open source repo for an ML accelerator that performed both inference and training None of us have real professional experience in hardware design, which, in a way, made the TPU even more appealing since we weren't able to estimate exactly how difficult it would be. As we worked on the initial stages of this project, we…
2025 · tinytpu.com · its alternatives →
9GP
GAN Playground – Play with Generative Adversarial Neural Nets In-Browser▲97
2017 · reiinakano.github.io · its alternatives →
10
A competition for small neural networks that play strategy gamesfree▲116
A ranked ladder for small neural networks that play strategy games. Train a model, write an adapter, upload two files, and get measured into a weight class from 8 KiB up.
Sep 2026 · tinybrains.dev · its alternatives →
11
TensorFire▲99
Blazing-fast in-browser neural networks
2017 · tenso.rs · its alternatives →
12
Unity 3d Neuroevolution Flappy Bird▲68
Unity C# Flappy Bird + Neuroevolution. WebGl demo: http://nfb.gametroleum.com - KrzysztofBogdan/CsNeuroevolutionFlappyBird
2017 · github.com · its alternatives →
13
Multi-GPU Reinforcement Learning in Tensorflow for OpenAI Gym▲58
Multi-GPU reinforcement learning using Deep Q-Network in TensorFlow for OpenAI Gym - vishar0/dist-dqn
2016 · github.com · its alternatives →
14
Evolly▲82
Framework that helps AI researchers design better models
2023 · github.com · its alternatives →
15
LeanRL: Fast PyTorch RL with Torch.compile and CUDA Graphs▲53
We're excited to announce that we've open-sourced LeanRL, a lightweight PyTorch reinforcement learning library that provides recipes for fast RL training using torch.compile and CUDA graphs. By leveraging these tools, we've achieved significant speed-ups compared to the original CleanRL implementations - up to 6x faster! Reinforcement learning is notoriously CPU-bound due to the high frequency of small CPU operations. PyTorch's powerful compiler can help alleviate these issues, but comes with its own costs. LeanRL addresses this challenge by providing simple recipes to accelerate your…
2024 · github.com · its alternatives →
16
I built a deep learning engine from scratch in Python▲30
I’ve spent the last few months building a deep learning engine completely from scratch in Python (using only math and random). What started as a basic linear algebra calculator project grew into a symbolic tensor system with autodiff, custom matrix ops, attention mechanisms, LayerNorm, GELU, and even a text generation demo trained on the Brown corpus. I'm still an undergrad, so my main goal is to deeply understand how deep learning actually works under the hood - gradients, attention, backpropagation, optimizers - by building it step-by-step with full visibility into everything, and without…
2025 · github.com · its alternatives →
17
MLGarden, a tool/toy to build and train simple neural networks visually▲11
I made this tool to get some better intuition on how neural networks/backpropagation worked, but I'm really unsure what to do with it now, so I've put it up on github, and I wrote a little primer on backprop and neural networks to showcase it. Really curious to hear any thoughts you might have, or anything I got wrong in the write up!
2024 · github.com · its alternatives →
18
DeepSwarm – Optimising CNNs Using Swarm Intelligence▲73
Neural Architecture Search Powered by Swarm Intelligence 🐜 - Pattio/DeepSwarm
2019 · github.com · its alternatives →
19
A perceptron with stochastic gradient descent in Go▲94
A single / multi layer / recurrent neural network written in Golang. - made2591/go-perceptron-go
2017 · github.com · its alternatives →
20
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 →
21
Bender – a Deep Learning framework for iOS▲81
Easily craft fast Neural Networks on iOS! Use TensorFlow models. Metal under the hood. - xmartlabs/Bender
2017 · github.com · its alternatives →
22
TensorFlow 1.0▲80
Open-source machine learning library by Google
2018 · tensorflow.org · its alternatives →
23
Layered – Neural Networks in Python 3▲56
Clean implementation of feed forward neural networks - danijar/layered
2015 · github.com · its alternatives →
24
Automatic Induction of Machine Code by Genetic Programming▲26
An AIMGP (Automatic Induction of Machine code by Genetic Programming) engine - evoasm/evoasm.rb
2016 · github.com · its alternatives →

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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →