AI · head to head
Rev vs scikit-learn
Rev
AI
Human and AI transcription, captions and subtitles priced per minute
- From
- Free
- Free plan
- Yes
The short version
- Each has a real cost: 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.; scikit-learn no GPU acceleration by default; limited optional GPU support requires external arrays
- They diverge on capability: Rev covers Human transcription, scikit-learn covers Classification algorithms.
- Prices and features above were last checked on 31 August 2026.
Where they differ
Only the attributes on which Rev and scikit-learn actually diverge.
| Attribute | Rev | scikit-learn |
|---|---|---|
| Pricing model | Per minute for human work, per seat per month for AI | Unknown |
| Platforms | Web, iOS, Android, API | Python, Linux, macOS, Windows |
| Category | AI | Machine Learning |
| Founded | Unknown | 2007 |
Identical on both: starting price (Free), free tier (Yes), 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 Rev
- Human transcription
- AI transcription
- Captions and subtitles
- Legal transcripts
- File analysis
- Clio integration
- Rev API
- Speaker identification
Only in scikit-learn
- Classification algorithms
- Regression models
- Clustering methods
- Dimensionality reduction
- Model selection
- NumPy
- SciPy
- Pandas
What people use each for
The jobs each tool is most often brought in to do.
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 scikit-learn
- 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 scikit-learn
- A broadcaster needing compliant human captions rather than machine captions, where accuracy is a regulatory requirement and not a convenience.not scikit-learn
- 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 scikit-learn
scikit-learn
- Machine learningnot Rev
- Data analysisnot Rev
- Model trainingnot Rev
- Predictive analyticsnot Rev
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
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.
scikit-learn
- No GPU acceleration by default; limited optional GPU support requires external arrays
- Single-machine only; no built-in distributed computing across clusters
- All datasets must fit entirely in RAM; no out-of-core learning
- No production-grade deep learning; neural network support limited to basic multilayer perceptron
- No reinforcement learning algorithms
Pricing, plan by plan
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
scikit-learn
FreeNo published plan breakdown. See the scikit-learn review.
Which should you pick?
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.
Choose scikit-learn if
- You need classification algorithms.
- You want to start without paying.
- You work on Python, Linux, macOS, Windows.
- You also want regression models.
Questions people ask
- Is Rev or scikit-learn better?
- Neither clearly leads. Rev starts at Free and scikit-learn at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Rev or scikit-learn?
- Rev starts at Free and scikit-learn at Free.
- Does Rev or scikit-learn run on more platforms?
- Rev runs on Web, iOS, Android, API. scikit-learn runs on Python, Linux, macOS, Windows.
- Can I use Rev for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Rev best used for?
- Rev is most often used for 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., 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., a broadcaster needing compliant human captions rather than machine captions, where accuracy is a regulatory requirement and not a convenience., 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.. Of those, 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. and 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. are not what scikit-learn is typically brought in for.
- What can Rev do that scikit-learn cannot?
- Rev covers Human transcription, AI transcription, Captions and subtitles, Legal transcripts. scikit-learn covers Classification algorithms, Regression models, Clustering methods, Dimensionality reduction.
Answered from the vendors’ own pages
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.
scikit-learn: Does scikit-learn support GPU acceleration?
Scikit-learn has no native GPU support by design to keep installation simple and cross-platform. Since 2023, a limited number of estimators can run on GPUs if input data is provided as PyTorch or CuPy arrays, but this requires additional setup.
SourceRev: Is there a free tier?
Yes, 45 AI minutes per month and up to 5 files analysed, with no human transcription included.
scikit-learn: Can scikit-learn handle datasets larger than RAM?
No. Scikit-learn is built on NumPy which requires all data to fit in memory, and NumPy operates on single-machine CPUs only. For very large datasets, consider Spark MLlib or distributed alternatives.
SourceRev: Do unused AI minutes roll over?
No. The allowance is per seat per month and resets, which penalises irregular workloads.
scikit-learn: Is scikit-learn free to use commercially?
Yes. Scikit-learn is open source under the BSD license, which allows free commercial use, modification, and distribution.
SourceRev: 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.
scikit-learn: What neural network capabilities does scikit-learn have?
Scikit-learn includes only a basic multilayer perceptron (MLPClassifier and MLPRegressor) for simple feedforward networks. For serious deep learning, use PyTorch, TensorFlow, or Keras instead.
SourceRev: 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.
scikit-learn: Does scikit-learn include natural language processing?
Scikit-learn has minimal NLP support limited to basic text feature extraction and vectorization. For comprehensive text processing, use spaCy or NLTK instead.
Sourcescikit-learn: When was scikit-learn first released?
Scikit-learn's first public release was February 1, 2010, following its start as a Google Summer of Code project in 2007.
SourceRelated pages
More on scikit-learn
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