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Software · head to head

Hugging Face vs Seldon

Hugging Face logo

Hugging Face

Software

The AI community building the future

From
Free
Rated
-
Full reviewWebsite
Seldon logo

Seldon

Software

Deploy, scale, and monitor machine learning models

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Hugging Face model discovery across 3 million models lacks robust filtering and sorting by quality metrics; 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: Hugging Face covers Model hub, Seldon covers Model serving.

Where they differ

Only the attributes on which Hugging Face and Seldon actually diverge.

Attributes where Hugging Face and Seldon differ
AttributeHugging FaceSeldon
Pricing modelUnknownfreemium
PlatformsWeb, APILinux
Founded20162014

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 Hugging Face

  • Model hub
  • Datasets
  • Spaces
  • Transformers library
  • GitHub
  • Cloud providers
  • MLOps tools
  • Web support

Only in Seldon

  • Model serving
  • A/B testing
  • Canary deployments
  • Outlier detection
  • Model explainability
  • Kubernetes
  • Istio
  • Prometheus

What people use each for

The jobs each tool is most often brought in to do.

Hugging Face

  • ai tools managementnot Seldon
  • Workflow automationnot Seldon
  • Reportingnot Seldon

Seldon

  • Serving and routing machine learning models on Kubernetesnot Hugging Face
  • Building multi-step inference pipelines with A/B tests and explainersnot Hugging Face

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Hugging Face

  • Model discovery across 3 million models lacks robust filtering and sorting by quality metrics
  • Community-driven content means variable model quality and documentation
  • Private models and datasets require Pro subscription
  • Enterprise support and SLAs require custom arrangements

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

Hugging Face

Free

No published plan breakdown. See the Hugging Face review.

Seldon

Free
  • Seldon CoreFree
    • Open source
    • Kubernetes deployment
    • Model serving
  • Seldon DeployFree
    • Enterprise features
    • GUI
    • Monitoring

Which should you pick?

Choose Hugging Face if

  • You need model hub.
  • You want to start without paying.
  • You work on Web, API.
  • You also want datasets.
Hugging Face review

Choose Seldon if

  • You need model serving.
  • You want to start without paying.
  • You work on Linux.
  • You also want a/b testing.
Seldon review

Questions people ask

Is Hugging Face or Seldon better?
Neither clearly leads. Hugging Face 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, Hugging Face or Seldon?
Hugging Face starts at Free and Seldon at Free.
Does Hugging Face or Seldon run on more platforms?
Hugging Face runs on Web, API. Seldon runs on Linux.
Can I use Hugging Face for free?
Both have a free tier, so you can try either at no cost before committing.
What is Hugging Face best used for?
Hugging Face is most often used for ai tools management, workflow automation, reporting. Of those, ai tools management and workflow automation are not what Seldon is typically brought in for.
What can Hugging Face do that Seldon cannot?
Hugging Face covers Model hub, Datasets, Spaces, Transformers library. Seldon covers Model serving, A/B testing, Canary deployments, Outlier detection.

Answered from the vendors’ own pages

Hugging Face: Is Hugging Face free to use?

Yes. Hugging Face allows users to host and collaborate on unlimited public models, datasets, and applications at no cost. Models can be accessed and used freely from the Hub.

Source
Hugging Face: How many models are available on Hugging Face?

Hugging Face Hub currently hosts nearly 3 million machine learning models across various tasks including text generation, image processing, and video generation.

Source
Hugging Face: What is the Hugging Face Inference API?

Hugging Face provides access to 45,000+ models from leading AI providers through a single unified API with no service fees, simplifying access to diverse models.

Source
Hugging Face: What content types does Hugging Face support?

Hugging Face supports text, image, video, audio, and 3D content models, allowing collaboration across multiple modalities and use cases.

Source
Hugging Face: What is the transformers library?

Transformers is a Hugging Face library built for natural language processing applications, providing pre-built models and utilities for NLP tasks.

Source
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Related pages

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