Software · head to head
PyTorch vs Seldon

PyTorch
Software
Deep learning framework with dynamic computation graphs
- From
- Free
- Rated
- -
The short version
- Each has a real cost: PyTorch dynamic computation graph can be less efficient for production inference than static graphs; Seldon production deployment requires a Kubernetes cluster, whether managed such as GKE, EKS or AKS, or on-premises such as OpenShift
- They diverge on capability: PyTorch covers Dynamic computation graphs, Seldon covers Model serving.
Where they differ
Only the attributes on which PyTorch and Seldon actually diverge.
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Unknown).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in PyTorch
- Dynamic computation graphs
- Automatic differentiation
- GPU acceleration
- Distributed training
- TorchScript
- TorchVision
- TorchText
- TorchAudio
Only in Seldon
- Model serving
- A/B testing
- Canary deployments
- Outlier detection
- Model explainability
- Kubernetes
- Istio
- Prometheus
Both cover
- Linux support
What people use each for
The jobs each tool is most often brought in to do.
PyTorch
- Machine learningnot Seldon
- Data analysisnot Seldon
- Model trainingnot Seldon
- Predictive analyticsnot Seldon
Seldon
- Serving and routing machine learning models on Kubernetesnot PyTorch
- Building multi-step inference pipelines with A/B tests and explainersnot PyTorch
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
PyTorch
- Dynamic computation graph can be less efficient for production inference than static graphs
- Requires more manual code for distributed training compared to some alternatives
- Documentation focused heavily on research use cases rather than production deployment
Seldon
- Production deployment requires a Kubernetes cluster, whether managed such as GKE, EKS or AKS, or on-premises such as OpenShift
- The documented components carry both minimum and maximum supported versions, so newer Kubernetes and dependency versions are not automatically supported
- Dataflow Pipelines need an additional component that the docs recommend avoiding installing when pipelines are not used
- The Docker Compose install is offered as a lightweight alternative for environments without Kubernetes rather than as a production path
Pricing, plan by plan
PyTorch
FreeNo published plan breakdown. See the PyTorch review.
Seldon
Free- Seldon CoreFree
- Open source
- Kubernetes deployment
- Model serving
- Seldon DeployFree
- Enterprise features
- GUI
- Monitoring
Which should you pick?
Choose PyTorch if
- You need dynamic computation graphs.
- You want to start without paying.
- You work on Linux, Windows, macOS.
- You also want automatic differentiation.
Choose Seldon if
- You need model serving.
- You want to start without paying.
- You work on Linux.
- You also want a/b testing.
Questions people ask
- Is PyTorch or Seldon better?
- Neither clearly leads. PyTorch starts at Free and Seldon at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, PyTorch or Seldon?
- PyTorch starts at Free and Seldon at Free.
- Does PyTorch or Seldon run on more platforms?
- PyTorch runs on Linux, Windows, macOS. Seldon runs on Linux.
- Can I use PyTorch for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is PyTorch best used for?
- PyTorch is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what Seldon is typically brought in for.
- What can PyTorch do that Seldon cannot?
- PyTorch covers Dynamic computation graphs, Automatic differentiation, GPU acceleration, Distributed training. Seldon covers Model serving, A/B testing, Canary deployments, Outlier detection. Both handle Linux support.
Answered from the vendors’ own pages
PyTorch: Is PyTorch free and open source?
Yes. PyTorch is an open source machine learning framework that is completely free to use. It was originally created and open-sourced by Facebook (now Meta) in 2016.
SourcePyTorch: What platforms does PyTorch support?
PyTorch supports Linux, Windows, and macOS. It provides strong GPU acceleration through CUDA and other backends for high-performance computing.
SourcePyTorch: Can I use PyTorch for production deployments?
Yes. PyTorch provides graph-based execution, distributed training, mobile deployment, and quantization features to support production deployments.
SourceRelated pages
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