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Machine Learning · head to head

Seldon vs Turbopack

Seldon logo

Seldon

Machine Learning

Kubernetes model serving whose current version is licensed under the Business Source Licence

From
Free
Rated
-
Full reviewWebsite
Turbopack logo

Turbopack

Web Development

Incremental bundler for JavaScript written in Rust

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Seldon seldon Core v2 is under the Business Source Licence rather than Apache 2.0, so production use requires a commercial agreement, and a team that evaluated it believing it was open source discovers the licence is the blocker exactly when the project is ready to ship.; Turbopack effectively coupled to Next.js; using it standalone is not the supported path
  • They diverge on capability: Seldon covers Kubernetes custom resources, Turbopack covers Incremental computation.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Seldon and Turbopack actually diverge.

Attributes where Seldon and Turbopack differ
AttributeSeldonTurbopack
Pricing modelfreemiumOpen source, no licence fee
PlatformsLinuxLinux, macOS, Windows
CategoryMachine LearningWeb Development
Founded2014Unknown

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).

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 Seldon

  • Kubernetes custom resources
  • Inference graphs
  • Traffic strategies
  • Open Inference Protocol
  • Alibi Explain
  • Alibi Detect
  • Kafka-backed pipelines in v2
  • Commercial control plane

Only in Turbopack

  • Incremental computation
  • Written in Rust
  • Next.js integration
  • Fast refresh

What people use each for

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

Seldon

  • Serving an ensemble or a multi-stage inference path as one versioned deployment rather than as a chain of separate servicesnot Turbopack
  • Running genuine production experiments where a share of live traffic goes to a candidate model and the results are comparednot Turbopack
  • Regulated environments needing explanations and drift monitoring attached to the served model rather than bolted on laternot Turbopack
  • Organisations with an established Kubernetes platform team who want serving expressed as manifests under existing deployment controlsnot Turbopack

Turbopack

  • Large Next.js applications where rebuild time is the daily costnot Seldon
  • Teams already on Vercel’s stack wanting faster local feedbacknot Seldon
  • Migrating off webpack within Next.js without changing frameworksnot Seldon

Where each one falls short

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

Seldon

  • Seldon Core v2 is under the Business Source Licence rather than Apache 2.0, so production use requires a commercial agreement, and a team that evaluated it believing it was open source discovers the licence is the blocker exactly when the project is ready to ship.
  • Core v1 remains Apache 2.0 but is in maintenance, so taking the free route means running software that receives no new development while the architecture it belongs to moves on without it.
  • Version 2 is a different system rather than a newer release, with different custom resources, a scheduler component and a Kafka-based pipeline model, so migrating from v1 is a re-implementation of every deployment manifest rather than an upgrade.
  • Kafka is a dependency for v2 pipelines, so an organisation that does not already operate it takes on a distributed log with its own storage, retention, rebalancing and failure modes purely in order to serve models.
  • Everything assumes Kubernetes fluency and the failure modes are Kubernetes failure modes, custom resource version mismatches, an operator that will not reconcile, admission webhooks and resource limits terminating an inference pod mid-request, so it needs a platform engineer rather than a data scientist.

Turbopack

  • Effectively coupled to Next.js; using it standalone is not the supported path
  • Younger than the alternatives, and ecosystem plugin support is narrower than webpack’s
  • Benchmark claims have been contested publicly, so measure on your own project rather than trusting headline numbers
  • Being Vercel-driven ties its roadmap to one company’s framework priorities

Pricing, plan by plan

Seldon

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

Turbopack

Free
  • TurbopackFree
    • Full functionality
    • Commercial use permitted
    • Community support

Which should you pick?

Choose Seldon if

  • You need kubernetes custom resources.
  • You want to start without paying.
  • You work on Linux.
  • You also want inference graphs.
Seldon review

Choose Turbopack if

  • You need incremental computation.
  • You want to start without paying.
  • You work on Linux, macOS, Windows.
  • You also want written in rust.
Turbopack review

Questions people ask

Is Seldon or Turbopack better?
Neither clearly leads. Seldon starts at Free and Turbopack at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Seldon or Turbopack?
Seldon starts at Free and Turbopack at Free.
Does Seldon or Turbopack run on more platforms?
Seldon runs on Linux. Turbopack runs on Linux, macOS, Windows.
Can I use Seldon for free?
Both have a free tier, so you can try either at no cost before committing.
What is Seldon best used for?
Seldon is most often used for serving an ensemble or a multi-stage inference path as one versioned deployment rather than as a chain of separate services, running genuine production experiments where a share of live traffic goes to a candidate model and the results are compared, regulated environments needing explanations and drift monitoring attached to the served model rather than bolted on later, organisations with an established kubernetes platform team who want serving expressed as manifests under existing deployment controls. Of those, serving an ensemble or a multi-stage inference path as one versioned deployment rather than as a chain of separate services and running genuine production experiments where a share of live traffic goes to a candidate model and the results are compared are not what Turbopack is typically brought in for.
What can Seldon do that Turbopack cannot?
Seldon covers Kubernetes custom resources, Inference graphs, Traffic strategies, Open Inference Protocol. Turbopack covers Incremental computation, Written in Rust, Next.js integration, Fast refresh.

Answered from the vendors’ own pages

Seldon: Is Seldon open source?

Partly, and this is the thing to check before you build on it. Core v1 is Apache 2.0 but in maintenance. Core v2 was moved to the Business Source Licence in 2024, which allows evaluation but not unlicensed production use. Verify the current licence of each component you intend to run, including MLServer and the Alibi libraries.

Turbopack: Is Turbopack free?

Yes, open source from Vercel.

Seldon: What is the difference between v1 and v2?

Architecture, not just version number. v2 introduces a scheduler, a different set of custom resources and Kafka-backed pipelines. Manifests, mental model and operations all change, so treat a move as a project.

Turbopack: Can I use Turbopack without Next.js?

Not really. It is developed as the Next.js bundler, and standalone use is not the supported path.

Seldon: Do I need Kubernetes?

Yes. It is a Kubernetes-native system and there is no meaningful deployment without a cluster and someone competent to run it.

Turbopack: Is Turbopack faster than Vite?

It depends on the project, and published comparisons have been disputed by both sides. Measure on your own codebase rather than relying on headline figures.

Seldon: What is MLServer?

Seldon's Python inference server implementing the Open Inference Protocol, usable inside Seldon deployments or on its own. Check its current licence alongside Core's, since the company has moved projects onto the Business Source Licence.

Seldon: Do I have to run Kafka?

For v2 pipelines, yes. If you only need single models served, that dependency is a large amount of infrastructure for the benefit, and a simpler serving layer may be the better answer.

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