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Machine Learning · head to head

OpenAI API vs Weka

OpenAI API logo

OpenAI API

Machine Learning

Hosted API for OpenAI's language, embedding, image and audio models, billed per token

From
$0.15/per-million-tokens
Rated
-
Full reviewWebsite
Weka logo

Weka

Machine Learning

Collection of machine learning algorithms

From
Free
Rated
-
Full reviewWebsite

The short version

  • Only Weka has a free tier, so it costs nothing to try first.
  • Each has a real cost: OpenAI API cost scales with tokens rather than with seats, so a successful feature's bill grows with its adoption, and an interface that lets users paste long documents has no natural ceiling on spend unless you build one yourself.; Weka the package management system needs an internet connection to download and install packages, so an air-gapped install gets only the core distribution
  • They diverge on capability: OpenAI API covers Text and reasoning models, Weka covers Classification.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which OpenAI API and Weka actually diverge.

Attributes where OpenAI API and Weka differ
AttributeOpenAI APIWeka
Starting price$0.15/per-million-tokensFree
Pricing modelusage-basedopen-source
Free tierNoYes
PlatformsApiLinux, Mac, Windows
Founded20151993

Identical on both: user rating (Not yet rated), category (Machine Learning).

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 OpenAI API

  • Text and reasoning models
  • Embeddings
  • Speech and audio
  • Image generation
  • Function calling
  • Structured outputs
  • Batch processing
  • Prompt caching

Only in Weka

  • Classification
  • Regression
  • Clustering
  • Association rules
  • Feature selection
  • Java
  • R
  • Python

What people use each for

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

OpenAI API

  • Adding summarisation, drafting or classification to an existing product where building a model would take longer than the product's whole roadmapnot Weka
  • Retrieval-augmented question answering over internal documents, using the embedding and generation models togethernot Weka
  • Extracting structured records from unstructured text, where schema-constrained output removes most of the parsing problemnot Weka
  • Prototyping a language feature quickly to find out whether it is worth the cost of a self-hosted alternative laternot Weka

Weka

  • Teaching and exploring classic machine learning algorithms through a GUInot OpenAI API
  • Running data mining experiments and preprocessing without writing codenot OpenAI API

Where each one falls short

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

OpenAI API

  • Cost scales with tokens rather than with seats, so a successful feature's bill grows with its adoption, and an interface that lets users paste long documents has no natural ceiling on spend unless you build one yourself.
  • Models are deprecated on the vendor's timetable, and a fine-tuned model built on a retired base goes with it, so the tuning work and the data curation behind it must be redone rather than migrated.
  • Behaviour shifts between model versions in ways no test catches unless you wrote one, so prompts tuned over months against a particular snapshot can regress quietly on migration, which makes an evaluation suite a prerequisite rather than an improvement.
  • It cannot run inside your own network, so data residency requirements, air-gapped environments and contracts forbidding third-party processing rule it out regardless of the provider's own security posture.
  • You inherit its availability and its rate limits, so a provider incident is an outage in your product and a traffic spike can be throttled at precisely the moment the feature is proving itself.

Weka

  • The package management system needs an internet connection to download and install packages, so an air-gapped install gets only the core distribution
  • Weka is split into a stable 3.8 branch that receives only bug fixes and compatibility-safe upgrades and a 3.9 development branch that may receive features that break compatibility
  • Weka requires a 64-bit Java VM; the bundled installers ship Bellsoft OpenJDK 25 per platform and architecture

Pricing, plan by plan

OpenAI API

$0.15/per-million-tokens
  • GPT-4o mini$0.15/per-million-input-tokens
    • Fast
    • Affordable
  • GPT-4o$5/per-million-input-tokens
    • Multimodal
    • 128K context

Weka

Free
  • Open SourceFree
    • All ML algorithms
    • GUI and CLI
    • Java API

Which should you pick?

Choose OpenAI API if

  • You need text and reasoning models.
  • You work on Api.
  • You also want embeddings.
OpenAI API review

Choose Weka if

  • You need classification.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want regression.
Weka review

Questions people ask

Is OpenAI API or Weka better?
Neither clearly leads. OpenAI API starts at $0.15/per-million-tokens and Weka at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, OpenAI API or Weka?
Weka has a free tier; the other does not. Paid plans start at $0.15/per-million-tokens for OpenAI API and Free for Weka.
Does OpenAI API or Weka run on more platforms?
OpenAI API runs on Api. Weka runs on Linux, Mac, Windows.
Can I use Weka for free?
Yes. Weka has a free tier, so you can try it without paying. OpenAI API starts at $0.15/per-million-tokens.
What is OpenAI API best used for?
OpenAI API is most often used for adding summarisation, drafting or classification to an existing product where building a model would take longer than the product's whole roadmap, retrieval-augmented question answering over internal documents, using the embedding and generation models together, extracting structured records from unstructured text, where schema-constrained output removes most of the parsing problem, prototyping a language feature quickly to find out whether it is worth the cost of a self-hosted alternative later. Of those, adding summarisation, drafting or classification to an existing product where building a model would take longer than the product's whole roadmap and retrieval-augmented question answering over internal documents, using the embedding and generation models together are not what Weka is typically brought in for.
What can OpenAI API do that Weka cannot?
OpenAI API covers Text and reasoning models, Embeddings, Speech and audio, Image generation. Weka covers Classification, Regression, Clustering, Association rules.

Answered from the vendors’ own pages

OpenAI API: Is my data used to train the models?

API inputs and outputs are not used for training by default, which differs from the consumer product. Retention periods and enterprise terms change, so read the current data usage policy rather than trusting a summary.

Weka: What is the cost of Weka software?

Weka is provided at no cost as open-source software released under the GNU General Public License, making it freely available for download and use.

Source
OpenAI API: Can I run these models on my own hardware?

No. The weights are not distributed. If self-hosting is a requirement, you are looking at open-weight models instead, with the operational and quality trade-offs that implies.

Weka: Are there commercial licensing options available?

Yes, the project offers information about commercial licenses for organizations requiring non-GPL terms, which can be found in their commercial applications documentation.

Source
OpenAI API: How is it priced?

Per token, with input and output priced differently and each model priced differently. Batch processing and cached input prefixes reduce it. The practical consequence is that your bill is a function of prompt design, not just of request count.

Weka: What support resources are available to users?

Multiple support avenues exist including comprehensive documentation, frequently asked questions, dedicated help resources, and access to courses for learning the platform.

Source
OpenAI API: What is the difference from Azure OpenAI Service?

The same model family delivered by Microsoft under an Azure contract, with Azure identity, networking and regional controls, and a different release cadence for new models. Enterprises with an Azure agreement often choose it for procurement and data residency reasons rather than technical ones.

Weka: Is source code access provided?

Yes, developers have full access to source code through the Git repository, along with development documentation and code credits for contributors.

Source
OpenAI API: How do I keep the cost under control?

Cap input length, cache repeated prefixes, route easy requests to smaller models, use the batch path where latency does not matter, and set per-user limits before launch rather than after the first surprising invoice.

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