Alternatives

Products that do what Zant – A TinyML SDK in Zig does

Hey HN, We’re excited to announce Zant v0.1, an open-source TinyML SDK built in Zig, designed to optimize and deploy neural networks on resource-constrained devices. Unlike existing solutions, Zant focuses on performance, portability, and ease of integration, making it a strong alternative for anyone working on Edge AI and embedded ML. Why Zant? Most TinyML frameworks are either too high-level (requiring bloated runtimes) or too low-level (requiring extensive manual optimization). Zant bridges the gap by offering: - A lightweight but powerful code generation system to translate ML models…

1
MakeML▲274
Train Neural Networks without a line of code
2019
2NO
Nous – Open-Source Agent Framework with Autonomous, SWE Agents, WebUI▲155
Hello HN! The day has finally come to stop adding features and start sharing what I've been building the last 5-6 months. It's a bit of CrewAI, OpenDevon, LangFuse/Cloud all in one, providing devs who prefer TypeScript an integrated framework thats provides a lot out of the box to start experimenting and building agents with. It started after peeking at the LangChain docs a few times and never liking the example code. I began experimenting with automating a simple Jira request from the engineering team to add an index to one of our Google Spanner databases (for context I'm the…
2024 · github.com
3
ZenML▲84
Create reproducible machine learning pipelines
2020
4LB
Lowdefy – Build internal tools with YAML on an open-source framework▲107
2021 · lowdefy.com
5ZM
Zig monthly: iOS support, tutorials, tree-sitter, and more▲33
2021 · zigmonthly.org
6ZE
ZenML, extensible open-source MLOps framework for reproducible ML▲37
2020 · github.com
7ZA
zcrun – a minimal Linux container runtime in Zig▲5
2024 · github.com
8ZZ
ZDS – Zig Data Structures▲5
A collection of high-performance data structures for Zig.
Dec 2025 · github.com
9E0
Element 0 – A small embeddable Lisp written in Zig▲5
Hi everyone, I've made a new experimental Lisp dialect (named "Element 0"). It comes with an interpreter written in Zig and a small standard library. The project is open source, and feedback is welcome. Project's GitHub repo: https://github.com/habedi/element-0
Sep 2025
10MA
Minigrad – a small neural network lib in Golang▲9
I built a neural network library in golang on an autograd engine. Faster and easy to use like PyTorch. Please give it a try and share your feedback. if you like it, a github star will be appreciated.
2024 · github.com
11TN
The No-Code Tool I built for my own AI Experiments▲5
Hi guys, I’m excited to share an update on ReproModel, an open-source toolbox designed to streamline the testing and reproduction of machine learning models. I, like many of you, have really struggled with benchmarking and comparing models, from missing code, to opaque experiment parameters slowing the process. I decided to take matters into my own hands, and created a mini-toolbox in my free time to streamline the process. The goal is to reduce the time and effort spent on replicating experiments, enabling researchers to focus on innovation rather than setup. Knowing this task is not an…
2024 · github.com
12CA
Chilli – A lightweight microframework for CLIs in Zig▲7
I've made an open-source microframework for creating command-line (CLI) applications in the Zig programming language. It's called Chilli, and it currently provides the following features: - A declarative API for defining nested commands, flags, and positional arguments. - Type-safe parsing of arguments from the command line and environment variables. - Automatic generation of formatted `--help` and `--version` output. - Support for command aliases, persistent flags, and other common CLI patterns. You can find the project on GitHub: https://github.com/habedi/chilli
2025
13PR
Prompt-refiner – Lightweight optimization for LLM inputs and RAG▲7
Hi HN, While building RAG agents, I noticed a lot of token budget was wasted on formatting overhead (HTML tags, JSON structure, whitespace). Existing solutions felt too heavy (often requiring torch/transformers), so I wrote this lightweight, zero-dependency library to solve it. It includes strategies for context packing, PII redaction, and tool output compression. Benchmarks show it can save ~15% of tokens with negligible latency overhead (<0.5ms). Happy to answer any questions!
Dec 2025 · github.com
14IC
I created a Neural Network from scratch, in scratch▲7
I spent the past week implementing a 1 Layer Neural Net and training it on MNIST within the visual scripting language provided by scratch.mit.edu. It was tedious, but ultimately not too difficult. The code runs incredibly slowly, so much so that 64 samples of MNIST takes 5+ hours to train on my machine. There were a lot of little mini challenges that were fun to overcome (implementing softmax was very tricky). If you're interested, I encourage you to try and improve on it! More details in the linked blog post.
2024 · bell-boy.github.io
15K4
KrillClaw – 49KB AI agent runtime in Zig for $3 microcontrollers▲8
Feb 2026 · github.com
16SP
Swift-powered AI apps on iOS: Real-time multimodal semantic search▲6
I was recently playing with Apple's CoreML and had several painful observations on tooling. It's not enough for a long read but should be for an HN post. In short, you can take a simple BERT-like encoder model in PyTorch, convert it into an f32 CoreML checkpoint, and run it on CPU or GPU, but not NPU. Let's unpack this. Having a simple and extensible format to exchange common ANN architectures is a big issue for anyone who uses more than one framework or programming language to run the same model. ONNX is the closest we have to that standard, but it's hard to call anything Protobuf-related…
2024 · github.com
17LR
Linear RNN/Reservoir hybrid generative model, one C file (no deps.)▲7
I just noticed it takes literally ~5 minutes to train millions parameters on slow CPU...but before you call Yudkowsky that "it's over", an important note: the main bottleneck is the corpus size, params are just 'cleverness' but given limited info it's powerless. Anyway, here is the project: https://github.com/bggb7781-collab/lrnnsmdds/tree/main couple of notes: 1. single C file, no dependencies. Below are literally all the "dependencies", not even custom header (copy paste from the top of the single c file): #define _POSIX_C_SOURCE 200809L #include #include…
Apr 2026 · raw.githubusercontent.com
18SO
Simon – open-source automated machine learning▲5
Hello HN crowd, I would love to show you open source project I've been working on for the last year or bit more, SIMON (https://github.com/genular/simon-frontend) In short, it is an autoML platform, with a primary goal to be used as a knowledge discovery application. This is an initial release of it so you can consider it as heavy beta :) You can check it and read more about it on the project GitHub page, or on the official website (https://genular.org) If you wish you can check screenshots of the SIMON here…
2019
19OA
OctopusGarden – An autonomous software factory (specs in, code out)▲8
I built this over the weekend after reading about StrongDM's software factory (their writeup: https://factory.strongdm.ai/, Simon Willison's deep dive: https://simonwillison.net/2026/Feb/7/software-factory/, Dan Shapiro's Five Levels: https://www.danshapiro.com/blog/2026/01/the-five-levels-from...). OctopusGarden is an open-source implementation of the pattern StrongDM described: holdout scenarios, probabilistic satisfaction scoring via LLM-as-judge, and a convergence loop that iterates until the code works; no…
Mar 2026 · github.com
20WB
We built an AI Website builder with better output▲8
Hey HN, After GPT-3 created waves in the tech industry, a lot of AI tools were emerging and with that, some AI website builders But the results seemed way too generic to us. It felt like the developers were rushing to catch the wave instead of building a proper tool We took our time, did months of RnD and finally came up with something better than what others in the market are doing. It’s got better design output. While it’s still in beta, I wanted to show HN what we did. Will appreciate the feedback when you guys try it out. Here is the link to signup for the beta:…
2024 · dorik.com
21AT
Automated Testing for AI Agents▲8
Hi Hacker News! We're launching Zalor, an agent testing platform. Agents often break when you tweak system prompts, swap models, or add tools. Zalor automatically generates test scenarios and evaluates your agent so you know it's reliable before deploying to production. We currently support the OpenAI Agents SDK and are onboarding other frameworks. A GitHub integration is coming so you can get feedback on every update. Looking forward to hearing feedback from people building agents.
Mar 2026 · agents.zalor.ai
22WU
WhiteLightning – ultra-lightweight ONNX text classifiers trained w LLMs▲8
Hey HN, We’re Volodymyr and Volodymyr—two developers from Ukraine building WhiteLightning. It’s a tool that turns large LLMs (Claude 4, Grok 4, GPT-4o via OpenRouter) into tiny ONNX text classifiers that run anywhere—even on drones at the edge. Why we built this: Many developers want custom models (spam filters, sentiment analysis, PII detection, moderation tools), but don’t want to deal with constant API calls or deploy heavy models in production. How it works: WhiteLightning uses LLMs to generate training data and distills it into KB-sized ONNX models you can run on any device and in any…
2025 · whitelightning.ai
23GA
Grav, an Open Source Flat-File CMS▲7
2014 · getgrav.org
24IB
I "built" Sana, a vector DB on object storage▲5
Disclaimer it is a heavily AI assisted project. The goal was not to be the most performative but the kind that's easier to learn from. I wanted to share this in case there are people who had the same idea or wanted to see something like this.
Jun 2026 · github.com

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