Tech riderRev. 4 Oct 2026
Ray Train
- 1Runs onLinux, Mac, self-hosted, Windows
- 2CostsFree plan
- 3Training modeboth
- 4Deployment targetsmultiple
- 5GPU accelerationYes
- 6Distributed trainingYes
- 7Supported languagesPython
7 lines stated Written from the maker's own pages: ray.io
Overview
Ray Train is ranked #10 of 36 in deep learning software on Specifiction. It runs on Linux, macOS, Self-hosted, Windows. There is a free plan.
Ray Train plans and pricing
All plansRay Train Free Pricing is not stated on the product pages reviewed; Ray is described as open source. ray.io · 4 Oct 2026
Compared on deep learning software
Facts
- Purpose
- Ray Train distributes model training compute to worker processes across a Ray cluster.docs.ray.io · 4 Oct 2026
- Framework integrations
- Ray Train integrates with PyTorch, PyTorch Lightning, Hugging Face Transformers, XGBoost, JAX, DeepSpeed, TensorFlow and Keras, LightGBM, and Horovod.docs.ray.io · 4 Oct 2026
- Data integration
- Ray Train integrates with Ray Data for streaming data loading and preprocessing, and also supports framework-native data utilities such as PyTorch Dataset and Hugging Face Dataset.docs.ray.io · 4 Oct 2026
- Scaling
- The homepage says Ray can scale from a laptop to thousands of GPUs and use heterogeneous GPUs and CPUs with independent scaling.ray.io · 4 Oct 2026
- Training workloads
- The homepage describes distributed training for generative AI foundation models, time-series models, and traditional machine-learning models such as XGBoost.ray.io · 4 Oct 2026
- Workers and resources
- Ray Train uses a training function, workers, a scaling configuration with CPU or GPU resources, and a Trainer to execute a distributed training job.docs.ray.io · 4 Oct 2026
- Preprocessing
- Ray Data can distribute heavy preprocessing across CPU nodes so it does not bottleneck GPU training, and Ray Train can split data across workers on the fly.docs.ray.io · 4 Oct 2026
- Monitoring
- Ray Train provides user guides for monitoring and logging metrics during training.docs.ray.io · 4 Oct 2026
- Experiment tracking
- Ray Train has an experiment tracking user guide.docs.ray.io · 4 Oct 2026
- Security
- Ray supports built-in token authentication starting in version 2.52.0, while its security guidance calls for controlled networks and trusted code.docs.ray.io · 4 Oct 2026
- Security limitation
- Ray does not provide isolation between jobs or access controls for developers within a cluster; its security guidance recommends separate clusters where workload isolation is required.docs.ray.io · 4 Oct 2026
- Support
- The Ray site offers a community Slack, forums, and documentation, and says Anyscale offers hands-on training and expert support.ray.io · 4 Oct 2026
- Intended users
- Ray’s security documentation describes Ray developers running local single-node clusters or remote multi-node clusters on infrastructure provided by platform providers.docs.ray.io · 4 Oct 2026
Best Ray Train alternatives
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Where it ranks on Specifiction
- Best Deep Learning Software in 2026#10 of 36
Is Ray Train yours?
Claim it for free: prove the domain, then correct facts, plans and screenshots. An editor reviews every change.
Sources
- docs.ray.io/en/latest/train/overview.html· checked 4 Oct 2026
- docs.ray.io/en/latest/train/user-guides/data-loadin· checked 4 Oct 2026
- ray.io· checked 4 Oct 2026
- docs.ray.io/en/latest/train/user-guides/monitoring-· checked 4 Oct 2026
- docs.ray.io/en/latest/train/user-guides/experiment-· checked 4 Oct 2026
- docs.ray.io/en/master/ray-security/index.html· checked 4 Oct 2026