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AI · head to head

Banana vs Ray

Banana logo

Banana

AI

ML inference at scale

From
$1200/month
Free plan
No
Full reviewWebsite
Ray logo

Ray

Machine Learning

Scale AI and Python applications

From
Free
Free plan
Yes
Full reviewWebsite

The short version

  • Only Ray 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; Ray windows support is beta and multi node Ray clusters are untested on Windows
  • They diverge on capability: Banana covers GPU inference, Ray covers Distributed computing.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Banana and Ray actually diverge.

Attributes where Banana and Ray differ
AttributeBananaRay
Starting price$1200/monthFree
Pricing modelsubscriptionfreemium
Free tierNoYes
PlatformsCloud, ApiLinux, Mac, Windows
CategoryAIMachine Learning
Founded20212019

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 Ray

  • Distributed computing
  • Ray Train
  • Ray Tune
  • RLlib
  • Ray Serve
  • PyTorch
  • TensorFlow
  • Hugging Face

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 Ray
  • Migration reference for teams that ran models on Banana before the 2024 shutdownnot Ray

Ray

  • Distributed AI model training and servingnot Banana
  • Large-scale data processingnot Banana
  • Reinforcement learning workloadsnot Banana
  • ML inference servingnot 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

Ray

  • Windows support is beta and multi node Ray clusters are untested on Windows
  • Windows lacks copy on write forking, which raises memory requirements, and Ray code assumes UNIX filenames
  • Multi node clusters are untested on Apple Silicon Macs
  • The Java API is experimental and community supported only, and requires matching Java and Python versions
  • Python 3.13 support is beta

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

Ray

Free
  • Open SourceFree
    • Full Ray framework
    • All libraries
    • Community support
  • Anyscale PlatformFree
    • Managed infrastructure
    • Enterprise support
    • SLAs

Which should you pick?

Choose Banana if

  • You need gpu inference.
  • You work on Cloud, Api.
  • You also want auto-scaling.
Banana review

Choose Ray if

  • You need distributed computing.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want ray train.
Ray review

Questions people ask

Is Banana or Ray better?
Neither clearly leads. Banana starts at $1200/month and Ray at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Banana or Ray?
Ray has a free tier; the other does not. Paid plans start at $1200/month for Banana and Free for Ray.
Does Banana or Ray run on more platforms?
Banana runs on Cloud, Api. Ray runs on Linux, Mac, Windows.
Can I use Ray for free?
Yes. Ray 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 Ray is typically brought in for.
What can Banana do that Ray cannot?
Banana covers GPU inference, Auto-scaling, Docker deployment, Low latency. Ray covers Distributed computing, Ray Train, Ray Tune, RLlib.

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
Ray: Is Ray free?

Yes. Ray is free and open source software with over 34,800 GitHub stars and 1,000+ contributors. Users can download and use the Ray framework at no cost.

Source
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
Ray: Is there a paid option for Ray?

Yes. Anyscale, the managed platform built by Ray's creators, offers paid tiers with enterprise features like governance and advanced tooling. Specific Anyscale pricing details are not listed on the Ray website.

Source
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
Ray: Can I try Ray with credits?

Yes. New users can try Ray with $100 credit on Anyscale's managed platform to explore the service.

Source
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