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AI · head to head

Replicate vs Seldon

Replicate logo

Replicate

AI

Run AI models in the cloud

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: Replicate private model deployments are billed for all the time instances are online, including setup and idle time, not only for processing; 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: Replicate covers Model hosting, Seldon covers Kubernetes custom resources.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Replicate and Seldon actually diverge.

Attributes where Replicate and Seldon differ
AttributeReplicateSeldon
Pricing modelusage-basedfreemium
PlatformsApi, CloudLinux
CategoryAIMachine Learning
Founded20192014

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 Replicate

  • Model hosting
  • Simple API
  • Auto-scaling
  • Custom models
  • REST API
  • Python client
  • JavaScript client
  • Api support

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.

Replicate

  • Running open source machine learning models through a hosted API without managing GPUsnot Seldon
  • Deploying and serving a custom or fine tuned model on rented GPU hardwarenot Seldon
  • Per second billed batch image, video and language model inferencenot Seldon

Seldon

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

Where each one falls short

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

Replicate

  • Private model deployments are billed for all the time instances are online, including setup and idle time, not only for processing
  • Multi-GPU A100, H100, H200 and L40S capacity beyond the listed configurations is only available with a committed spend contract
  • The pricing page publishes no free tier allowance

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

Replicate

Free
  • Pay-as-you-go$null/usage
    • Billed by execution time for public models
    • CPU Small: $0.000025/second ($0.09/hour)
    • 8x Nvidia A100 GPUs: $0.0112/second ($40.32/hour)
  • Enterprise$null/custom
    • Dedicated account manager
    • Priority support
    • Higher GPU limits

Seldon

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

Which should you pick?

Choose Replicate if

  • You need model hosting.
  • You want to start without paying.
  • You work on Api, Cloud.
  • You also want simple api.
Replicate 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 Replicate or Seldon better?
Neither clearly leads. Replicate 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, Replicate or Seldon?
Replicate starts at Free and Seldon at Free.
Does Replicate or Seldon run on more platforms?
Replicate runs on Api, Cloud. Seldon runs on Linux.
Can I use Replicate for free?
Both have a free tier, so you can try either at no cost before committing.
What is Replicate best used for?
Replicate is most often used for running open source machine learning models through a hosted api without managing gpus, deploying and serving a custom or fine tuned model on rented gpu hardware, per second billed batch image, video and language model inference. Of those, running open source machine learning models through a hosted api without managing gpus and deploying and serving a custom or fine tuned model on rented gpu hardware are not what Seldon is typically brought in for.
What can Replicate do that Seldon cannot?
Replicate covers Model hosting, Simple API, Auto-scaling, Custom models. Seldon covers Kubernetes custom resources, Inference graphs, Traffic strategies, Open Inference Protocol.

Answered from the vendors’ own pages

Replicate: How much does Replicate cost?

Replicate uses pay-as-you-go pricing based on model execution time and compute type. Costs range from $0.09/hour for CPU (Small) to $40.32/hour for 8x Nvidia A100 GPUs. Some models charge per input/output tokens instead of time.

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.

Replicate: Does Replicate offer a free tier?

Yes, Replicate is free to start with pay-as-you-go pricing. There are no subscription tiers or minimum commitments; you pay only for what you use.

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.

Replicate: What is the difference between public and private models?

Public models are billed by execution time. Private models are billed for all instance uptime including setup, idle, and active processing time, except for fast-booting fine-tunes which are billed only during active processing.

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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