Determined
Determined: A focused option for teams training distributed models on their own infrastructure. Ranked #7 of 22 in Experiment Tracking by our editors (8.2/10); pricing: Free plan; best for teams training distributed models on their own.
At a glance
- Editor score8.2 / 10
- PricingFree plan
- Best forTeams training distributed models on their own
- Free planYes
- Paid fromFree
- Founded2020
- Facts checked23 Sep 2026
Where it wins
- Tracks code versions, metrics, checkpoints, and hyperparameters
- Combines distributed training with GPU scheduling and resource management
- Supports deployments to AWS, GCP, Kubernetes, and Slurm/PBS
Where it doesn't
- Experiment tracking is narrower than leading suites
- Workflows are centered on Python
- Support is community-based
Our verdict on Determined
Determined brings distributed training, hyperparameter tuning, experiment tracking, and resource management into an open-source deep learning platform. It is aimed at researchers and machine learning teams that train models on their own clusters or deploy training workloads across cloud and cluster environments. Experiment records include code versions, metrics, checkpoints, and hyperparameters, while the Web UI covers experiment and cluster monitoring. The fit is strongest for teams that want training operations and tracking together rather than a broad, standalone tracking suite.
The platform works with PyTorch and TensorFlow and offers a Python library and command-line interface for experiment creation and training. Its deployment options include AWS and GCP, as well as Kubernetes and Slurm/PBS; it can run on local clusters too. That range suits teams with varied infrastructure, but the working model remains Python-centered. Teams standardizing on other languages or looking primarily for tracking breadth may prefer an alternative with a wider tracking feature set.
Determined is open source and has a free plan, with deployments available in cloud and self-hosted environments. The published product details describe GPU scheduling, resource utilization visibility, logs, and model registry information through the Web UI, but do not establish a tier-by-tier paid plan structure. Community support is the listed support channel, so organizations that require a specified vendor support arrangement should weigh that in their evaluation. Choose Determined when distributed training, infrastructure control, and core experiment records are central; look elsewhere if a richer tracking suite is the priority.
Your product? Our editors can test Determined in depth and publish a review, labelled as paid · from $149/mo →
Determined pricing
Determined fact sheet
| Free plan | Yes |
|---|---|
| Paid from | Free |
| Self-hosted option | Not verified |
| Artifact storage | Not verified |
| Run comparison | Not verified |
| Free plan seats | Not verified |
| Version control | Not verified |
| Deployment options | Not verified |
| Deployment | Cloud, Self-hosted |
| Platforms | Web, Linux |
| Support | Community |
| Built for | Small business, Mid-market, Enterprise (editorial estimate) |
| Integrations | 6 integrations: PyTorch, TensorFlow, AWS, GCP, Kubernetes, Slurm/PBS |
| Pricing | Free plan |
| Website | hpe.com |
| Facts checked | 23 Sep 2026 |
Determined integrations
Determined lists 6 integrations on its own site.
- PyTorch
- TensorFlow
- AWS
- GCP
- Kubernetes
- Slurm/PBS
Alternatives to Determined
- Weights & BiasesA broad tracking platform for teams that need experiments, registry, and serving in one place.8.9
- CometA detailed experiment-tracking workspace with run comparisons, versioned artifacts, and a model registry.8.7
- ClearMLA broad experiment-tracking and MLOps toolkit with hosted and self-hosted options.8.6
See all Determined alternatives →
Determined vs the competition
- Determined vs Weights & Biases
- Determined vs Comet
- Determined vs ClearML
- Determined vs Databricks Mosaic AI
- Determined vs Amazon SageMaker AI
- Determined vs Valohai
Compare Determined with any tool side by side →
Also Ranked In
Determined is ranked in 2 of our directories.
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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