AI · alternatives · 2026

24 alternatives to Model Zoo

Deploy your machine learning model in a single line of code.

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Model Zoo launched in 2020; newer entries below may have overtaken it.

1MZ
Model Zoo: Deploy your machine learning model in a single line of code▲34
Informasi Akurat, Berita Terupdate – Hanya di Sini
2020 · modelzoo.dev · its alternatives →
2
Modelbit▲125
Heroku for Data Science, from the founders of Periscope Data
2023 · modelbit.com · its alternatives →
3
Inferless▲749
Deploy any machine learning models in minutes
2025 · inferless.com · its alternatives →
4
Zoo▲234
A free, open-source playground for AI image models
2023 · zoo.replicate.dev · its alternatives →
5
Deploy ML Models on a Budget▲117
Deploy a ML inference service on a budget in less than 10 lines of code. - ebhy/budgetml
2021 · github.com · its alternatives →
6
Gradient Zoo▲63
Version and share your trained neural network models
2016 · its alternatives →
7
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 →
8
Comprehensive Tutorials in Deep Learning Using TensorFlow▲327
:satellite: Simple and ready-to-use tutorials for TensorFlow - GitHub - instillai/TensorFlow-Course: :satellite: Simple and ready-to-use tutorials for TensorFlow
2018 · github.com · its alternatives →
9
Machine learning automation from creating to using models in production▲72
a delightful machine learning tool that allows you to train, test, and use models without writing code - GitHub - nidhaloff/igel at v0.4.0
2021 · github.com · its alternatives →
10
Pretrained AI▲144
Integrate pretrained machine learning models in minutes.
2021 · pretrained.ai · its alternatives →
11
TensorZero▲307
Hi HN! We're Gabriel & Viraj, and we're excited to open source TensorZero. To be a little cheeky, TensorZero is an open-source platform that helps LLM applications graduate from API wrappers into defensible AI products. 1. Integrate our model gateway 2. Send metrics or feedback 3. Unlock compounding improvements in quality, cost, and latency It enables a data & learning flywheel for LLMs by unifying: • Inference: one API for all LLMs, with <1ms P99 overhead • Observability: inference & feedback → your database • Optimization: better prompts, models, inference strategies • Experimentation:…
2025 · github.com · its alternatives →
12
Roboflow Universe▲237
Pre-trained computer vision models and public datasets
2021 · universe.roboflow.com · its alternatives →
13
Plexe▲273
Build and deploy ML models in English
2025 · plexe.ai · its alternatives →
14
Weights & Biases▲110
Developer tools for deep learning & machine learning
2019 · wandb.ai · its alternatives →
15CR
Carton – Run any ML model from any programming language▲196
The goal of Carton is to let you use a single interface to run any machine learning model from any programming language. It’s currently difficult to integrate models that use different technologies (e.g. TensorRT, Ludwig, TorchScript, JAX, GGML, etc) into your application, especially if you’re not using Python. Even if you learn the details of integrating each of these frameworks, running multiple frameworks in one process can cause hard-to-debug crashes. Ideally, the ML framework a model was developed in should just be an implementation detail. Carton lets you decouple your application from…
2023 · carton.run · its alternatives →
16
Truss – Serve any ML model without boilerplate code▲68
The simplest way to serve AI/ML models in production - basetenlabs/truss
2022 · github.com · its alternatives →
17MM
MLEM – ML model deployment tool▲24
Hi, I'm one of the project creators. MLEM is a tool that helps you deploy your ML models. It’s a Python library + Command line tool. 1. MLEM can package an ML model into a Docker image or a Python package, and deploy it to, for example, Heroku. 2. MLEM saves all model metadata to a human-readable text file: Python environment, model methods, model input & output data schema and more. 3. MLEM helps you turn your Git repository into a Model Registry with features like ML model lifecycle management. Our philosophy is that MLOps tools should be built using the Unix approach - each tool solves a…
2022 · its alternatives →
18
Fritz▲161
Mobile machine learning made easy
2018 · fritz.ai · its alternatives →
19
MLConsole – web app to train ML models, for free and client-side▲86
ML Console is a free tool to build an AI model without writing a single line of code. Simply pick a column to predict, and let us handle the rest.
2021 · mlconsole.com · its alternatives →
20
Zoo Design Studio v1.0▲140
Professional CAD platform + Text-to-CAD powered by ML
2025 · zoo.dev · its alternatives →
21CI
Convect – Instant Serverless Deployment of ML Models▲89
2021 · convect.ml · its alternatives →
22
Cortex▲81
Deploy, manage, and scale machine learning applications
2019 · its alternatives →
23
Fritz for Android▲24
Mobile machine learning made simple, now on Android.
2018 · fritz.ai · its alternatives →
24
Bodywork▲58
Deploy machine learning into production 🚀
2021 · 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 →