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Machine Learning · head to head

BigQuery ML vs Verbit

BigQuery ML logo

BigQuery ML

Machine Learning

Machine learning in BigQuery using SQL

From
Free
Free plan
Yes
Full reviewWebsite
Verbit logo

Verbit

AI

Transcription and captioning combining automatic speech recognition with professional human correction

From
$24/month
Free plan
No
Full reviewWebsite

The short version

  • Only BigQuery ML has a free tier, so it costs nothing to try first.
  • Each has a real cost: BigQuery ML not available in BigQuery's Standard edition, so the cheapest tier cannot use it; Verbit only a small self-service tier has a published price; the institutional plans that most education buyers actually need are quoted, so budgeting requires a sales cycle and comparison against competitors requires several.
  • They diverge on capability: BigQuery ML covers SQL-based ML, Verbit covers ASR with human correction.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which BigQuery ML and Verbit actually diverge.

Attributes where BigQuery ML and Verbit differ
AttributeBigQuery MLVerbit
Starting priceFree$24/month
Pricing modelusage-basedPer month by transcription hours
Free tierYesNo
PlatformsWebWeb, API
CategoryMachine LearningAI
Founded2008Unknown

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 BigQuery ML

  • SQL-based ML
  • AutoML Tables
  • Model export
  • Prediction functions
  • Feature preprocessing
  • BigQuery
  • Vertex AI
  • TensorFlow

Only in Verbit

  • ASR with human correction
  • Live realtime captioning
  • Domain-tuned models
  • Translation and subtitling
  • Audio description
  • LMS and video platform integrations
  • Court-admissible transcripts
  • Turnaround tiers

What people use each for

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

BigQuery ML

  • Training models in SQL without exporting datanot Verbit
  • Linear and logistic regression on warehouse datanot Verbit
  • K-means clustering and matrix factorisation for recommendationsnot Verbit
  • Time series forecasting with ARIMA_PLUSnot Verbit
  • Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot Verbit

Verbit

  • A university that must caption recorded teaching to meet accessibility law and wants machine output for general content with human correction only where a student accommodation appliesnot BigQuery ML
  • A broadcaster needing live realtime captioning to regulatory standard, which the VITAC operation supplies rather than a pure software vendornot BigQuery ML
  • A law firm or court reporting operation needing certified transcripts of depositions with a defensible chain of accuracynot BigQuery ML
  • A market research team transcribing focus groups where speaker separation and verbatim fidelity matter more than turnaround speednot BigQuery ML

Where each one falls short

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

BigQuery ML

  • Not available in BigQuery's Standard edition, so the cheapest tier cannot use it
  • Billed through BigQuery compute and storage rather than as its own product, so training cost tracks data scanned
  • Remote models incur extra Agent Platform charges on top
  • Externally trained model types such as boosted trees and AutoML run through Agent Platform rather than inside BigQuery

Verbit

  • Only a small self-service tier has a published price; the institutional plans that most education buyers actually need are quoted, so budgeting requires a sales cycle and comparison against competitors requires several.
  • Accuracy claims are benchmarked on clean audio with standard accents, and real lecture theatre recordings with technical vocabulary and non-native speakers fall well short, so the contracted level and the audio assumptions behind it must be written into the agreement.
  • The human correction layer is what delivers the accuracy institutions buy, and it introduces turnaround times measured in hours or days, which does not suit anyone expecting transcripts immediately after a session.
  • Cost scales with hours of content, so an institution that recorded everything during remote teaching and never reduced the volume can find transcription costing more than the lecture capture platform generating the recordings.
  • Verbit has grown by acquisition and consolidated several transcription brands, and customers of acquired services have been migrated onto Verbit contracts and pricing on the acquirer's timetable rather than their own.

Pricing, plan by plan

BigQuery ML

Free
  • Free TierFree
    • 10GB storage
    • 1TB queries
  • On-Demand$5/TB
    • Pay per TB scanned
    • ML training costs

Verbit

$24/month
  • Standard$24/month
    • From $24 per month
    • 100 hours per month split as 50 live and 50 post-production
    • Self-service sign-up
  • Campus Complete$undefined/year
    • Unlimited hours for an institution
    • Built around media accessibility obligations
    • LMS and lecture capture integrations
  • Legal Capture and Legal Visor$undefined/year
    • Unlimited legal transcription with court-admissible transcripts on request
    • Live AI transcription and case insights
    • Quoted
  • Custom$undefined/year
    • Enterprise deployment across the product suite
    • Negotiated accuracy levels and turnaround
    • Quoted

Which should you pick?

Choose BigQuery ML if

  • You need sql-based ml.
  • You want to start without paying.
  • You also want automl tables.
BigQuery ML review

Choose Verbit if

  • You need asr with human correction.
  • You work on Web, API.
  • You also want live realtime captioning.
Verbit review

Questions people ask

Is BigQuery ML or Verbit better?
Neither clearly leads. BigQuery ML starts at Free and Verbit at $24/month, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery ML or Verbit?
BigQuery ML has a free tier; the other does not. Paid plans start at Free for BigQuery ML and $24/month for Verbit.
Does BigQuery ML or Verbit run on more platforms?
BigQuery ML runs on Web. Verbit runs on Web, API.
Can I use BigQuery ML for free?
Yes. BigQuery ML has a free tier, so you can try it without paying. Verbit starts at $24/month.
What is BigQuery ML best used for?
BigQuery ML is most often used for training models in sql without exporting data, linear and logistic regression on warehouse data, k-means clustering and matrix factorisation for recommendations, time series forecasting with arima_plus. Of those, training models in sql without exporting data and linear and logistic regression on warehouse data are not what Verbit is typically brought in for.
What can BigQuery ML do that Verbit cannot?
BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions. Verbit covers ASR with human correction, Live realtime captioning, Domain-tuned models, Translation and subtitling.

Answered from the vendors’ own pages

BigQuery ML: How much does Google Cloud BigQuery ML cost?

BigQuery ML pricing is not specified separately on Google Cloud's pricing page. It follows the same pay-as-you-go model as BigQuery, charging per terabyte of data scanned during analysis. Customers receive $300 in free credits and can use 20+ products free up to monthly limits.

Source
Verbit: Is there published pricing?

Only for the entry Standard tier at around $24 a month for 100 hours split between live and post-production. Campus Complete and the legal and media unlimited plans are quoted.

BigQuery ML: Does Google Cloud offer a free trial?

Yes, new customers get $300 in free credits and all customers can use 20+ Google Cloud products free up to their monthly usage limits.

Source
Verbit: What accuracy does Verbit deliver?

Machine-only output is materially less accurate than the corrected tiers. Accuracy is a contracted service level on the human-corrected plans, and it assumes reasonable audio quality. Negotiate the figure and the remedy, not the marketing number.

Verbit: What is VITAC?

A large North American broadcast captioning business Verbit acquired in 2021. It is why Verbit can supply live realtime captioning at broadcast standard rather than only post-production transcripts.

Verbit: Can I mix machine and human transcription?

Yes, and it is the main reason education buyers choose Verbit: route routine content through machine processing and accommodation-covered content through human correction on the same account.

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