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BigQuery ML vs Deepgram

BigQuery ML logo

BigQuery ML

Machine Learning

Machine learning in BigQuery using SQL

From
Free
Free plan
Yes
Full reviewWebsite
Deepgram logo

Deepgram

AI

Voice AI API platform for speech-to-text, text-to-speech, and voice agents

From
Free
Free plan
Yes
Full reviewWebsite

The short version

  • Each has a real cost: BigQuery ML not available in BigQuery's Standard edition, so the cheapest tier cannot use it; Deepgram pricing is entirely usage-based, so total cost can be harder to predict than flat subscription tools.
  • They diverge on capability: BigQuery ML covers SQL-based ML, Deepgram covers Flux speech-to-text.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

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

Attributes where BigQuery ML and Deepgram differ
AttributeBigQuery MLDeepgram
PlatformsWebweb, api
CategoryMachine LearningAI
Founded2008Unknown

Identical on both: starting price (Free), pricing model (usage-based), 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 BigQuery ML

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

Only in Deepgram

  • Flux speech-to-text
  • Flux text-to-speech
  • Voice Agent API
  • Real-time and batch processing
  • Self-hosted deployment
  • Audio intelligence

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 Deepgram
  • Linear and logistic regression on warehouse datanot Deepgram
  • K-means clustering and matrix factorisation for recommendationsnot Deepgram
  • Time series forecasting with ARIMA_PLUSnot Deepgram
  • Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot Deepgram

Deepgram

  • Building real-time voice agents for customer supportnot BigQuery ML
  • Transcribing recorded audio at scale via batch STTnot BigQuery ML
  • Adding conversational text-to-speech to voice applicationsnot BigQuery ML
  • Self-hosting speech models for data residency requirementsnot 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

Deepgram

  • Pricing is entirely usage-based, so total cost can be harder to predict than flat subscription tools.
  • The Growth plan requires a minimum $4K/year commitment to unlock discounted rates.
  • Enterprise features and custom SLAs require a direct sales conversation rather than self-serve signup.
  • Some promotional per-minute rates are time-limited, meaning long-term pricing may differ from current promotional rates.

Pricing, plan by plan

BigQuery ML

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

Deepgram

Free
  • Pay As You Go$undefined/mo
    • $200 free credit to start
    • No minimums or expiration
    • No credit card required to start
  • Growth$undefined/mo
    • Save up to 20% with annual pre-paid credits
    • Minimum $4K/year commitment
    • Credits applied against actual usage
  • Enterprise$undefined/mo
    • Custom pricing for large-scale deployments
    • Dedicated support and contracts

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 Deepgram if

  • You need flux speech-to-text.
  • You want to start without paying.
  • You work on web, api.
  • You also want flux text-to-speech.
Deepgram review

Questions people ask

Is BigQuery ML or Deepgram better?
Neither clearly leads. BigQuery ML starts at Free and Deepgram at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery ML or Deepgram?
BigQuery ML starts at Free and Deepgram at Free.
Does BigQuery ML or Deepgram run on more platforms?
BigQuery ML runs on Web. Deepgram runs on web, api.
Can I use BigQuery ML for free?
Both have a free tier, so you can try either at no cost before committing.
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 Deepgram is typically brought in for.
What can BigQuery ML do that Deepgram cannot?
BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions. Deepgram covers Flux speech-to-text, Flux text-to-speech, Voice Agent API, Real-time and batch processing.

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
Deepgram: What does Deepgram cost?

Deepgram uses usage-based pricing starting with $200 in free credit, pay-as-you-go rates per minute or per character, a Growth plan with annual pre-paid credits requiring a $4K/year minimum, and custom Enterprise pricing.

Source
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
Deepgram: Is there a free plan, and what are its limits?

New users get $200 of free credit with no credit card required, which can be applied to speech-to-text, text-to-speech, or voice agent usage before any payment is needed.

Source
Deepgram: How is usage metered?

Usage is metered per minute of audio for speech-to-text and voice agent calls, and per 1,000 characters for text-to-speech, with add-ons like redaction and entity detection billed separately per minute.

Source
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