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Machine Learning · head to head

OpenAI API vs Rev

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
Free plan
No
Full reviewWebsite
Rev logo

Rev

AI

Human and AI transcription, captions and subtitles priced per minute

From
Free
Free plan
Yes
Full reviewWebsite

The short version

  • Only Rev 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.; Rev human transcription at 1.99 US dollars a minute means roughly 120 dollars an hour of audio, so a long-form interview series costs more in transcription than most teams assume before they run the arithmetic.
  • They diverge on capability: OpenAI API covers Text and reasoning models, Rev covers Human transcription.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

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

Attributes where OpenAI API and Rev differ
AttributeOpenAI APIRev
Starting price$0.15/per-million-tokensFree
Pricing modelusage-basedPer minute for human work, per seat per month for AI
Free tierNoYes
PlatformsApiWeb, iOS, Android, API
CategoryMachine LearningAI
Founded2015Unknown

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 OpenAI API

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

Only in Rev

  • Human transcription
  • AI transcription
  • Captions and subtitles
  • Legal transcripts
  • File analysis
  • Clio integration
  • Rev API
  • Speaker identification

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 Rev
  • Retrieval-augmented question answering over internal documents, using the embedding and generation models togethernot Rev
  • Extracting structured records from unstructured text, where schema-constrained output removes most of the parsing problemnot Rev
  • Prototyping a language feature quickly to find out whether it is worth the cost of a self-hosted alternative laternot Rev

Rev

  • A law firm that needs a deposition transcript in a court-acceptable page format with a fixed turnaround and a published per-page price it can bill to a matter.not OpenAI API
  • A documentary or podcast producer costing a project in advance, because human transcription at a published per-minute rate makes the transcription line item a known number.not OpenAI API
  • A broadcaster needing compliant human captions rather than machine captions, where accuracy is a regulatory requirement and not a convenience.not OpenAI API
  • A team with high AI volume and occasional high-stakes files, using the subscription for the bulk and paying the discounted human rate only where accuracy matters.not 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.

Rev

  • Human transcription at 1.99 US dollars a minute means roughly 120 dollars an hour of audio, so a long-form interview series costs more in transcription than most teams assume before they run the arithmetic.
  • AI minutes are allocated per seat per month and do not roll over, so bursty workloads, which is how most media production actually behaves, waste allowance in quiet months and run out in busy ones.
  • The product direction has moved towards legal and investigative use, so a newsroom or media buyer is choosing a tool whose roadmap priority sits elsewhere.
  • Foreign-language subtitles are priced from 6.49 to 15.99 US dollars per minute, an order of magnitude above transcription, which makes multi-language localisation of any volume of video expensive enough to change the plan.
  • Human turnaround is stated in hours rather than guaranteed contractually on the published plans, so a hard broadcast or filing deadline needs an agreement beyond the standard terms.

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

Rev

Free
  • FreeFree
    • 45 AI transcription and caption minutes per month
    • Up to 5 files analysed
    • No human transcription included
  • Essentials$25.49/month
    • 5,000 AI minutes per seat per month
    • Up to 3 seats
    • 10 per cent discount on human transcription, captions and subtitles
  • Pro$47.99/month
    • 10,000 AI minutes per seat per month
    • Up to 5 seats
    • 15 per cent discount on human work
  • Unlimited$undefined/month
    • Unlimited AI minutes
    • Up to 500 files analysed at once
    • Dedicated account specialist

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 Rev if

  • You need human transcription.
  • You want to start without paying.
  • You work on Web, iOS, Android, API.
  • You also want ai transcription.
Rev review

Questions people ask

Is OpenAI API or Rev better?
Neither clearly leads. OpenAI API starts at $0.15/per-million-tokens and Rev at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, OpenAI API or Rev?
Rev has a free tier; the other does not. Paid plans start at $0.15/per-million-tokens for OpenAI API and Free for Rev.
Does OpenAI API or Rev run on more platforms?
OpenAI API runs on Api. Rev runs on Web, iOS, Android, API.
Can I use Rev for free?
Yes. Rev 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 Rev is typically brought in for.
What can OpenAI API do that Rev cannot?
OpenAI API covers Text and reasoning models, Embeddings, Speech and audio, Image generation. Rev covers Human transcription, AI transcription, Captions and subtitles, Legal transcripts.

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.

Rev: How much is human transcription?

1.99 US dollars per minute with a stated accuracy target above 99 per cent, typically returned within 12 hours. Subscribers get 10 to 15 per cent off.

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.

Rev: Is there a free tier?

Yes, 45 AI minutes per month and up to 5 files analysed, with no human transcription included.

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.

Rev: Do unused AI minutes roll over?

No. The allowance is per seat per month and resets, which penalises irregular workloads.

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.

Rev: Can it do subtitles in other languages?

Yes, across seventeen languages, priced from 6.49 to 15.99 US dollars per minute, considerably more than transcription.

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.

Rev: Is Rev still a good choice for newsrooms?

It works, but the subscription tiers are now positioned around legal and investigative workflows, so a newsroom should compare it against a tool built specifically for journalism.

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