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AI · head to head

RunPod vs Seldon

RunPod logo

RunPod

AI

GPU cloud for AI and ML

From
$0.2/per-hour
Free plan
No
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

  • Only Seldon has a free tier, so it costs nothing to try first.
  • Each has a real cost: RunPod idle volume disk storage is billed at $0.20 per GB per month, double the $0.10 per GB per month charged while the pod is running; 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: RunPod covers GPU instances, Seldon covers Kubernetes custom resources.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which RunPod and Seldon actually diverge.

Attributes where RunPod and Seldon differ
AttributeRunPodSeldon
Starting price$0.2/per-hourFree
Pricing modelusage-basedfreemium
Free tierNoYes
PlatformsCloud, ApiLinux
CategoryAIMachine Learning
Founded20222014

Identical on both: 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 RunPod

  • GPU instances
  • Serverless
  • Templates
  • Persistent storage
  • Docker
  • REST API
  • SSH access
  • Cloud 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.

RunPod

  • Renting GPU compute by the second for model training and inferencenot Seldon
  • Running serverless GPU workers that scale with request volumenot Seldon
  • Attaching persistent network storage shared across GPU podsnot Seldon

Seldon

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

Where each one falls short

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

RunPod

  • Idle volume disk storage is billed at $0.20 per GB per month, double the $0.10 per GB per month charged while the pod is running
  • Reserved clusters of all terms from 1 to 12 months are priced by contacting sales with no published rate
  • L40S, H100 SXM and B200 cluster configurations are listed as contact sales rather than at a published hourly rate
  • High performance network storage costs $0.14 per GB per month, twice the standard sub 1TB rate of $0.07

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

RunPod

$0.2/per-hour
  • Community Cloud$0.2/per-hour
    • Affordable GPUs
    • Spot instances
  • Secure Cloud$0.44/per-hour
    • Enterprise security
    • Dedicated hardware

Seldon

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

Which should you pick?

Choose RunPod if

  • You need gpu instances.
  • You work on Cloud, Api.
  • You also want serverless.
RunPod 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 RunPod or Seldon better?
Neither clearly leads. RunPod starts at $0.2/per-hour and Seldon at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, RunPod or Seldon?
Seldon has a free tier; the other does not. Paid plans start at $0.2/per-hour for RunPod and Free for Seldon.
Does RunPod or Seldon run on more platforms?
RunPod runs on Cloud, Api. Seldon runs on Linux.
Can I use Seldon for free?
Yes. Seldon has a free tier, so you can try it without paying. RunPod starts at $0.2/per-hour.
What is RunPod best used for?
RunPod is most often used for renting gpu compute by the second for model training and inference, running serverless gpu workers that scale with request volume, attaching persistent network storage shared across gpu pods. Of those, renting gpu compute by the second for model training and inference and running serverless gpu workers that scale with request volume are not what Seldon is typically brought in for.
What can RunPod do that Seldon cannot?
RunPod covers GPU instances, Serverless, Templates, Persistent storage. Seldon covers Kubernetes custom resources, Inference graphs, Traffic strategies, Open Inference Protocol.

Answered from the vendors’ own pages

RunPod: What is the pricing model for Runpod GPU compute?

Runpod uses usage-based pricing billed per second rather than fixed subscriptions. GPU pod pricing ranges from $0.27/hour for budget options like RTX A5000 to $7.89/hour for high-end options like B300. Serverless inference is billed based on worker usage.

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.

RunPod: Are there minimum contracts or commitments required to use Runpod?

No minimum contracts or commitments are required for on-demand services. Per-second billing is available, and you pay only for what you use. Long-term commitments offer additional savings through reserved capacity options.

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.

RunPod: What are the storage costs on Runpod?

Storage pricing is tiered: Container Disk costs $0.10/GB/month, Volume Disk costs $0.10/GB/month when running or $0.20/GB/month when idle, and Network Storage ranges from $0.05-$0.07/GB/month for standard to $0.14/GB/month for high-performance.

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.

RunPod: Does Runpod charge egress fees for data transfer?

No, Runpod does not charge egress fees when using persistent network storage, which helps reduce data transfer costs for workloads that need to move data in and out frequently.

Source
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.

RunPod: How does Runpod Serverless handle cold starts and idle costs?

Runpod Serverless offers zero idle cost and sub-200ms cold starts via FlashBoot technology. There is no warm-up tax, meaning you don't pay for idle capacity or accept cold-start latency penalties.

Source
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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