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AI · head to head

Galileo vs Seldon

Galileo logo

Galileo

AI

Evaluation and observability platform for GenAI applications and agents

From
Free
Free plan
Yes
Full reviewWebsite
Seldon logo

Seldon

Machine Learning

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

From
Free
Free plan
Yes
Full reviewWebsite

The short version

  • Each has a real cost: Galileo the free plan is limited to 5,000 traces per month, which is quickly outgrown by production workloads.; 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.
  • They diverge on capability: Galileo covers Pre-built evaluations, Seldon covers Kubernetes custom resources.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Galileo and Seldon actually diverge.

Attributes where Galileo and Seldon differ
AttributeGalileoSeldon
Platformsweb, apiLinux
CategoryAIMachine Learning
FoundedUnknown2014

Identical on both: starting price (Free), pricing model (freemium), 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 Galileo

  • Pre-built evaluations
  • Ground truth capture
  • Luna models
  • Agent behavior analysis
  • Production guardrails
  • Flexible deployment

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

What people use each for

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

Galileo

  • Evaluating RAG and agent applications before production releasenot Seldon
  • Monitoring live GenAI applications for failures and driftnot Seldon
  • Applying real-time guardrails without custom integration worknot Seldon
  • Reducing evaluation costs using distilled Luna judge modelsnot Seldon

Seldon

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

Where each one falls short

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

Galileo

  • The free plan is limited to 5,000 traces per month, which is quickly outgrown by production workloads.
  • Real-time guardrails and unlimited trace capacity are reserved for the custom-priced Enterprise tier.
  • Pro plan pricing scales with trace volume, so costs can grow unpredictably as usage increases.
  • On-premises deployment requires an Enterprise contract rather than being available self-serve.

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.

Pricing, plan by plan

Galileo

Free
  • FreeFree
    • 5,000 traces/month
    • Unlimited users
    • Unlimited custom evaluations
  • Pro$100/month
    • 50,000 traces/month
    • Standard role-based access control
    • Advanced analytics and insights
  • Enterprise$undefined/mo
    • Unlimited trace capacity
    • Custom rate limits
    • Hosted, VPC, or on-prem deployment

Seldon

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

Which should you pick?

Choose Galileo if

  • You need pre-built evaluations.
  • You want to start without paying.
  • You work on web, api.
  • You also want ground truth capture.
Galileo review

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

Questions people ask

Is Galileo or Seldon better?
Neither clearly leads. Galileo 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, Galileo or Seldon?
Galileo starts at Free and Seldon at Free.
Does Galileo or Seldon run on more platforms?
Galileo runs on web, api. Seldon runs on Linux.
Can I use Galileo for free?
Both have a free tier, so you can try either at no cost before committing.
What is Galileo best used for?
Galileo is most often used for evaluating rag and agent applications before production release, monitoring live genai applications for failures and drift, applying real-time guardrails without custom integration work, reducing evaluation costs using distilled luna judge models. Of those, evaluating rag and agent applications before production release and monitoring live genai applications for failures and drift are not what Seldon is typically brought in for.
What can Galileo do that Seldon cannot?
Galileo covers Pre-built evaluations, Ground truth capture, Luna models, Agent behavior analysis. Seldon covers Kubernetes custom resources, Inference graphs, Traffic strategies, Open Inference Protocol.

Answered from the vendors’ own pages

Galileo: What does Galileo cost?

Galileo offers a free plan, a Pro plan at $100/month billed yearly (with a 33% annual discount), and a custom-priced Enterprise plan for unlimited trace capacity.

Source
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.

Galileo: Is there a free plan, and what are its limits?

The Free plan includes 5,000 traces per month with unlimited users and unlimited custom evaluations, aimed at developers and small teams experimenting with GenAI.

Source
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.

Galileo: How is usage metered?

Galileo's pricing scales based on the number of traces processed each month, with Free capped at 5,000, Pro at 50,000, and Enterprise offering unlimited trace capacity.

Source
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.

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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