Deeplearning4j vs JAX
Deeplearning4j
deeplearning4j.konduit.aiJAX
docs.jax.devSide by side
| Figure | Deeplearning4j | JAX |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | — |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Deep Learning Software | 8.7 (#4) | 8.3 (#7) |
| Ecosystem | Its ecosystem includes ND4J, SameDiff, DataVec, Keras Import, Python4J, OmniHub, and Arbiter. | The documentation lists ecosystem tools including Flax, Keras, Optax, TensorFlow Datasets, Hugging Face Datasets and NumPyro. |
| Support | The support page lists GitHub issues, community forums, Stack Overflow, and professional support from Konduit. | The installation guide directs users with problems using prebuilt wheels to the JAX GitHub issue tracker. |
| What it does | Eclipse Deeplearning4j is an open-source deep learning framework for the JVM, for building, training, and deploying neural networks in Java and Scala. | JAX is a Python library for accelerator-oriented array computation and program transformation, designed for high-performance numerical computing and large-scale machine learning. |
Plans
In their own words
Deeplearning4j
Deeplearning4j is an open-source framework for building, training, and deploying neural networks on the JVM, using Java or Scala. It can compute on CPUs through OpenBLAS and oneDNN, or use CUDA for GPU acceleration. For distributed training, it supports Apache Spark across CPU or GPU clusters. The framework can import models from Keras, TensorFlow, and ONNX, while Python4J provides Python interoperability from Java through CPython embedding. Its wider ecosystem includes ND4J, SameDiff, DataVec, Keras Import, Python4J, OmniHub, and Arbiter. Documented deployment targets include JVM microservices, mobile devices, IoT, and Spark environments. The libraries are licensed under Apache License 2.0 and governed by the Eclipse Foundation. The quickstart recommends Maven for Java projects, with Ivy and Gradle also workable. Documentation covers version 1.0.0-M2.1. The free plan is listed at free. Support options include GitHub issues, community forums, Stack Overflow, and professional support from Konduit.