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Machine Learning · head to head

Seldon vs SolveSpace

Seldon logo

Seldon

Machine Learning

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

From
Free
Rated
-
Full reviewWebsite
S

SolveSpace

CAD

Open source parametric CAD with a constraint solver in a few megabytes

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.; SolveSpace the in-house geometry kernel fails on complex boolean operations and fillets, and the failure is sometimes silent bad geometry rather than an error message, so models must be checked before export or manufacture.
  • They diverge on capability: Seldon covers Kubernetes custom resources, SolveSpace covers Constraint solver.
  • Prices and features above were last checked on 1 September 2026.

Where they differ

Only the attributes on which Seldon and SolveSpace actually diverge.

Attributes where Seldon and SolveSpace differ
AttributeSeldonSolveSpace
Pricing modelfreemiumOpen source, no licence fee
PlatformsLinuxWindows, macOS, Linux
CategoryMachine LearningCAD
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 SolveSpace

  • Constraint solver
  • Solid modelling
  • Assemblies
  • Export formats
  • Cross-platform
  • Small footprint

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 SolveSpace
  • Running genuine production experiments where a share of live traffic goes to a candidate model and the results are comparednot SolveSpace
  • Regulated environments needing explanations and drift monitoring attached to the served model rather than bolted on laternot SolveSpace
  • Organisations with an established Kubernetes platform team who want serving expressed as manifests under existing deployment controlsnot SolveSpace

SolveSpace

  • Designing 3D printed parts on a machine that cannot run mainstream CADnot Seldon
  • Teaching constraint-based parametric modelling without buying licences for a classroomnot Seldon
  • Checking that a mechanical linkage moves as intended before cutting metalnot Seldon
  • Producing dimensionally accurate STEP or STL output from a small open source toolchainnot 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.

SolveSpace

  • The in-house geometry kernel fails on complex boolean operations and fillets, and the failure is sometimes silent bad geometry rather than an error message, so models must be checked before export or manufacture.
  • There is no proper drawing and dimensioning workflow, so manufacturing documentation has to be produced in another application.
  • Development is volunteer-led and intermittent; long gaps between releases are normal and there is no support contract available at any price.
  • Assembly-level import of external CAD is very limited, so it does not fit a supply chain that exchanges native or assembly-level models with suppliers.
  • The interface follows its own conventions rather than mainstream CAD ones, so existing SolidWorks or Fusion users spend time unlearning habits for a tool with a lower ceiling.

Pricing, plan by plan

Seldon

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

SolveSpace

Free
  • SolveSpaceFree
    • Full application under the GPL
    • No seat limit
    • Windows, macOS and Linux builds

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 SolveSpace if

  • You need constraint solver.
  • You want to start without paying.
  • You work on Windows, macOS, Linux.
  • You also want solid modelling.
SolveSpace review

Questions people ask

Is Seldon or SolveSpace better?
Neither clearly leads. Seldon starts at Free and SolveSpace at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Seldon or SolveSpace?
Seldon starts at Free and SolveSpace at Free.
Does Seldon or SolveSpace run on more platforms?
Seldon runs on Linux. SolveSpace runs on Windows, macOS, Linux.
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 SolveSpace is typically brought in for.
What can Seldon do that SolveSpace cannot?
Seldon covers Kubernetes custom resources, Inference graphs, Traffic strategies, Open Inference Protocol. SolveSpace covers Constraint solver, Solid modelling, Assemblies, Export formats.

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.

SolveSpace: Is it really free for commercial work?

Yes. It is released under the GPL with no licence fee and no seat limit. Support is community only.

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.

SolveSpace: Can it replace Fusion 360 or SolidWorks?

No. It handles parts and simple assemblies well. Complex geometry, drawings and supply chain interoperability are outside its range.

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.

SolveSpace: What hardware does it need?

Very little. It runs on old laptops and small Linux machines where mainstream CAD will not start.

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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