Alternatives

Products that do what Go-CoreML – Go Bindings for Apple's CoreML with Neural Engine Support does

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.

1
MakeML▲274
Train Neural Networks without a line of code
2019
2
IBM Watson for CoreML▲124
Apple's direct AI integration for iOS apps
2018
3
StackML▲252
Machine Learning platform in-browser, for creators
2019
4
Apple MLX▲138
An array framework for machine learning on Apple silicon
2023
5
Ollama▲235
The easiest way to run large language models locally
2023
6
Cai▲179
Press ⌥C on anything to run smart actions, locally
Apr 2026
7
Apple Core ML▲196
Integrate a broad variety of ML model types into your app
2017
8
OrchestraML▲82
From English prompt to deployed ML model with human approval
Jun 2026
9PO
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
10
npm i -g hotcell▲97
Local sandboxes for AI agents on your Mac, Linux, bare metal
Aug 2026 · github.com
11SP
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
12QB
Qt binding for Go with support for all major operating systems▲222
2017 · therecipe.github.io
13NL
Nice-looking Python bindings to V8▲166
2017 · github.com
14
NeuroBlock▲120
No-code AI Lab: Train models, access datasets, run inference
Feb 2026
15
Gowebly▲130
A next-generation CLI tool to build web apps easier
2024
16GS
GoJava – Server/desktop Java bindings to Go packages▲52
2016 · github.com
17
Nexa SDK▲130
Run, build & ship local AI in minutes
Sep 2025
18
ZenML▲84
Create reproducible machine learning pipelines
2020
19GB
Go Bindings for Roc Toolkit▲5
2023 · github.com
20
automl-docker▲68
Open-source, easily create ready-to-use ML models for NLP
2022
21
UnionML▲77
The easiest way to build and deploy ML microservices
2022
22
ScoopML▲81
An AI assistant for machine learning engineers
2020
23CD
Core Data Editor 4 (for OS X)▲16
2011 · christian-kienle.de
24OO
Osaurus – Ollama-Compatible Runtime for Apple Foundation Models▲6
Osaurus is an open-source local inference runtime for macOS, written in Swift and optimized for Apple Silicon. It lets you run Apple Foundation Models locally — fully accelerated by the Neural Engine — while also exposing OpenAI- and Ollama-compatible endpoints, so you can connect your favorite apps, tools, or clients without any code changes. Key points: * Supports Apple Foundation Models natively * Compatible with OpenAI & Ollama APIs * ~7 MB binary, runs locally (no cloud, no telemetry) * MIT Licensed, open source Project: https://osaurus.ai Source:…
Oct 2025 · github.com

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