Softwr

AI · head to head

Banana vs Seldon

Banana logo

Banana

AI

ML inference at scale

From
$1200/month
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: Banana banana shut down its serverless GPU infrastructure on 31 March 2024 at noon PST and told customers to migrate to another provider by that time; 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: Banana covers GPU inference, Seldon covers Kubernetes custom resources.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Banana and Seldon actually diverge.

Attributes where Banana and Seldon differ
AttributeBananaSeldon
Starting price$1200/monthFree
Pricing modelsubscriptionfreemium
Free tierNoYes
PlatformsCloud, ApiLinux
CategoryAIMachine Learning
Founded20212014

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 Banana

  • GPU inference
  • Auto-scaling
  • Docker deployment
  • Low latency
  • REST API
  • Python SDK
  • Cloud support
  • 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.

Banana

  • Historically, serverless GPU inference for machine learning modelsnot Seldon
  • Migration reference for teams that ran models on Banana before the 2024 shutdownnot Seldon

Seldon

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

Where each one falls short

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

Banana

  • Banana shut down its serverless GPU infrastructure on 31 March 2024 at noon PST and told customers to migrate to another provider by that time
  • The vendor's own sunset notice names limited runway, retention problems and GPU supply constraints as the reasons for closing
  • The banana.dev site still displays pricing tiers, but every tier links to the sunset notice rather than to a purchase

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

Banana

$1200/month
  • Team$1200/month
    • 10 team members
    • 5 projects
    • 50 max parallel GPUs
  • Enterprise$null/custom
    • Custom seat limit
    • Custom GPU configuration

Seldon

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

Which should you pick?

Choose Banana if

  • You need gpu inference.
  • You work on Cloud, Api.
  • You also want auto-scaling.
Banana 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 Banana or Seldon better?
Neither clearly leads. Banana starts at $1200/month and Seldon at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Banana or Seldon?
Seldon has a free tier; the other does not. Paid plans start at $1200/month for Banana and Free for Seldon.
Does Banana or Seldon run on more platforms?
Banana 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. Banana starts at $1200/month.
What is Banana best used for?
Banana is most often used for historically, serverless gpu inference for machine learning models, migration reference for teams that ran models on banana before the 2024 shutdown. Of those, historically, serverless gpu inference for machine learning models and migration reference for teams that ran models on banana before the 2024 shutdown are not what Seldon is typically brought in for.
What can Banana do that Seldon cannot?
Banana covers GPU inference, Auto-scaling, Docker deployment, Low latency. Seldon covers Kubernetes custom resources, Inference graphs, Traffic strategies, Open Inference Protocol.

Answered from the vendors’ own pages

Banana: How much does Banana's Team plan cost?

The Team plan costs $1,200 per month plus the cost of compute resources at cost with zero markup applied.

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.

Banana: What is the maximum team size on Banana's Team plan?

The Team plan includes 10 team members and supports a maximum of 5 projects with up to 50 parallel GPUs.

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.

Banana: Does Banana offer an Enterprise plan with custom pricing?

Banana offers an Enterprise plan with custom pricing plus at-cost compute, including SAML SSO, automation API, and dedicated support.

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.

Share

Related pages

More on Banana

More on Seldon

Keep looking

Other head to heads