AI · alternatives · 2026

24 alternatives to Go-CoreML – Go Bindings for Apple's CoreML with Neural Engine Support

Go bindings for CoreML that let you build and run ML models on Apple Silicon from Go, no Python required. You construct models programmatically using CoreML's MIL intermediate language, then run them on the Neural Engine, GPU, or CPU. Also works as a GoMLX backend.

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.

1
MakeML▲274
Train Neural Networks without a line of code
2019 · makeml.app · its alternatives →
2
IBM Watson for CoreML▲124
Apple's direct AI integration for iOS apps
2018 · developer.apple.com · its alternatives →
3
CLI for working with Apple Core ML models▲48
A native command-line interface for working with Apple Core ML models on macOS - schappim/coreml-cli
Jan 2026 · github.com · its alternatives →
4
Open-source engine running Gemma 4 26B in 2 GB RAM on any M-series Mac▲919
Hi HN, I built a specialized inference engine for running 4-bit Gemma 4 26B-A4B-IT on any M-series Mac using about 2 GB of RAM. It is called TurboFieldfare and is written in Swift and Metal. I have always adored on-device AI. It feels like magic that you can run a powerful NN on your Mac or iPhone. So I wanted to push the limits a bit and run a model whose weights don’t fit in memory. The model’s 4-bit quantized weights occupy roughly 14 GB, which makes running it with conventional inference tools almost impossible on an 8 GB or even 16 GB Mac once the OS, applications, and KV cache are…
Jul 2026 · github.com · its alternatives →
5
Ollama v0.19▲410
Massive local model speedup on Apple Silicon with MLX
Apr 2026 · ollama.com · its alternatives →
6
We made our own inference engine for Apple Silicon▲186
We wrote our inference engine on Rust, it is faster than llama cpp in all of the use cases. Your feedback is very welcomed. Written from scratch with idea that you can add support of any kernel and platform.
2025 · github.com · its alternatives →
7
StackML▲252
Machine Learning platform in-browser, for creators
2019 · its alternatives →
8QB
Qt binding for Go with support for all major operating systems▲222
Qt binding for Go (Golang) with support for Windows / macOS / Linux / FreeBSD / Android / iOS / Sailfish OS / Raspberry Pi / AsteroidOS / Ubuntu Touch / JavaScript / WebAssembly
2017 · therecipe.github.io · its alternatives →
9
Igel – A CLI tool to run machine learning without writing code▲405
a delightful machine learning tool that allows you to train, test, and use models without writing code - nidhaloff/igel
2020 · github.com · its alternatives →
10
Apple MLX▲138
An array framework for machine learning on Apple silicon
2023 · pypi.org · its alternatives →
11
Cai▲179
Hi HN, Cai runs actions on your selection via ⌥C, pick an action (AI, shell, GitHub issue, Linear ticket), done. Bundled local model (MLX Community), create custom actions with prompts, scripts and more. Free, MIT. Built after my Raycast extension sat in review queue for 3+ months. Wanted no typing, no app switching, no cloud. Repo: https://github.com/cai-layer/cai Demo: https://youtu.be/LH2MYNQ_wsk
Apr 2026 · getcai.app · its alternatives →
12
Ollama – Run LLMs on your Mac▲284
Hi HN A few folks and I have been working on this project for a couple weeks now. After previously working on the Docker project for a number of years (both on the container runtime and image registry side), the recent rise in open source language models made us think something similar needed to exist for large language models too. While not exactly the same as running linux containers, running LLMs shares quite a few of the same challenges. There are "base layers" (e.g. models like Llama 2), specific configuration to run correctly (parameters, temperature, context window sizes etc). There's…
2023 · github.com · its alternatives →
13
ML Shortcuts▲7
Use your own CoreML models to interact with your Mac
2025 · annotate.supply · its alternatives →
14PO
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 →
15
Ollama▲235
The easiest way to run large language models locally
2023 · github.com · its alternatives →
16
Run an 80B Qwen in 4.3 GB of RAM on a Mac, and a 35B on an iPhone▲312
Swiftlet is a Swift and Metal runtime that runs large Qwen Mixture-of-Experts models locally on Apple devices by streaming expert weights from storage, enabling 35B and 80B models to run with low RAM, including on iPhone. - leonickson1/Swiftlet
Aug 2026 · github.com · its alternatives →
17
Gradio 5.0▲224
connect nodes to build AI pipelines, powered by Hugging Face
2024 · gradio.app · its alternatives →
18
Apple Core ML▲196
Integrate a broad variety of ML model types into your app
2017 · developer.apple.com · its alternatives →
19
OrchestraML▲82
From English prompt to deployed ML model with human approval
Jun 2026 · orchestra-ml.vercel.app · its alternatives →
20
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 · its alternatives →
21
SwiftAI – open-source library to easily build LLM features on iOS/macOS▲74
We built SwiftAI, an open-source Swift library that lets you use Apple’s on-device LLMs when available (Apple opened access in June), and fall back to a cloud model when they aren’t available — all without duplicating code. SwiftAI gives you: - A single, model-agnostic API - An agent/tool loop - Strongly-typed structured outputs - Optional chat state Backstory: We started experimenting with Apple’s local models because they’re free (no API calls), private, and work offline. The problem: not all devices support them (older iPhones, Apple Intelligence disabled, low battery, etc.). That…
2025 · github.com · its alternatives →
22
GUIs for Faster ML Prototyping and Sharing▲85
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work! - gradio-app/gradio
2020 · github.com · its alternatives →
23
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 →
24
Web App with GUI for AutoML on Tabular Data▲41
AutoML Web App - build Machine Learning pipeline in automatic way with Graphical User Interface (GUI). You can run app locally! - mljar/automl-app
2023 · 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 →