Deeplearning4j vs Paperspace Gradient
Deeplearning4j
deeplearning4j.konduit.aiPaperspace Gradient
paperspace.comSide by side
| Figure | Deeplearning4j | Paperspace Gradient |
|---|---|---|
| Price from | Free | $8/mo |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | Yes |
| Web | — | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 17 |
| Spec score · Deep Learning Software | 8.7 (#4) | 8.8 (#3) |
| Compute | It provides native GPU acceleration via CUDA and CPU computation via OpenBLAS and oneDNN. | The platform offers on-demand GPU and IPU instances, with per-second instance pricing described on its product page. |
| Purpose | Eclipse Deeplearning4j is an open-source, distributed deep learning framework for the JVM. | Gradient is a machine learning platform for developing, tracking, and collaborating on machine learning models. |
| Support | The support page lists GitHub issues, community forums, Stack Overflow, and professional support from Konduit. | Paperspace lists free ticket-based support seven days a week and contract-based enterprise support with infrastructure assistance and customer success managers. |
| 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. | Paperspace is a cloud machine-learning platform for developing, training, and deploying AI applications with GPU-backed infrastructure. |
Plans
Paperspace Gradient
- Free (Individual)Free
- Pro (Individual)$8 a month
- Growth (Individual)$39 a month
- Free (Team)Free
- Pro (Team)$12 a month
- Growth (Team)$39 a month
- T0Free
- T1$12 a month
- FreeFree
- FreeFree
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.
Paperspace Gradient
Paperspace Gradient is a machine learning platform for building, tracking, and collaborating on models. Its browser-based IDE launches GPU-enabled Jupyter notebooks; teams can share projects, invite collaborators, and connect GitHub to manage code and compute resources. Notebook environments run in Docker containers. For deployment, Gradient serves models through API endpoints, with runtime, instance-type, and autoscaling choices. On-demand GPU and IPU instances are available, and paid instance utilization can cost extra beyond plan fees. Gradient supports major machine learning frameworks and libraries. Plans include free options and paid options listed from $8/mo; individual and team plans have different storage allowances, and notebook plans specify limits on notebooks and running sessions. Gradient is offered for beginners, ML/AI engineers, data scientists, researchers, teams, research groups, and startups. Paperspace also lists a Windows, macOS, and Linux beta desktop app, along with centralized permissions and activity logs.