Software · head to head
OpenAI API vs BigQuery ML
OpenAI API
Software
GPT and DALL-E APIs for developers
- From
- $0.15/per-million-tokens
- Rated
- -
The short version
- Only BigQuery ML has a free tier, so it costs nothing to try first.
- Each has a real cost: OpenAI API new accounts start with a $100 approved monthly usage limit and must spend cumulatively to graduate tiers; BigQuery ML not available in BigQuery's Standard edition, so the cheapest tier cannot use it
- They diverge on capability: OpenAI API covers GPT models, BigQuery ML covers SQL-based ML.
Where they differ
Only the attributes on which OpenAI API and BigQuery ML actually diverge.
| Attribute | OpenAI API | BigQuery ML |
|---|---|---|
| Starting price | $0.15/per-million-tokens | Free |
| Free tier | No | Yes |
| Platforms | Api | Web |
| Founded | 2015 | 2008 |
Identical on both: pricing model (usage-based), user rating (Not yet rated), category (Unknown).
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
- GPT models
- DALL-E
- Whisper
- Embeddings
- REST API
- SDKs
- Azure OpenAI
- Api support
Only in BigQuery ML
- SQL-based ML
- AutoML Tables
- Model export
- Prediction functions
- Feature preprocessing
- BigQuery
- Vertex AI
- TensorFlow
What people use each for
The jobs each tool is most often brought in to do.
OpenAI API
- Calling hosted language models from an applicationnot BigQuery ML
- Generating images, audio and embeddings through one APInot BigQuery ML
- Building agents and tool calling workflows on managed modelsnot BigQuery ML
BigQuery ML
- Training models in SQL without exporting datanot OpenAI API
- Linear and logistic regression on warehouse datanot OpenAI API
- K-means clustering and matrix factorisation for recommendationsnot OpenAI API
- Time series forecasting with ARIMA_PLUSnot OpenAI API
- Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot OpenAI API
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
OpenAI API
- New accounts start with a $100 approved monthly usage limit and must spend cumulatively to graduate tiers
- Reaching the top Tier 5 monthly cap of $200,000 requires $1,000 of cumulative paid usage
- Rate limits apply simultaneously across requests per minute, requests per day, tokens per minute, tokens per day and images per minute, and the first one hit blocks the request
- API access is restricted to approved geographies
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
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
BigQuery ML
Free- Free TierFree
- 10GB storage
- 1TB queries
- On-Demand$5/TB
- Pay per TB scanned
- ML training costs
Which should you pick?
Choose BigQuery ML if
- You need sql-based ml.
- You want to start without paying.
- You also want automl tables.
Questions people ask
- Is OpenAI API or BigQuery ML better?
- Neither clearly leads. OpenAI API starts at $0.15/per-million-tokens and BigQuery ML at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, OpenAI API or BigQuery ML?
- BigQuery ML has a free tier; the other does not. Paid plans start at $0.15/per-million-tokens for OpenAI API and Free for BigQuery ML.
- Does OpenAI API or BigQuery ML run on more platforms?
- OpenAI API runs on Api. BigQuery ML runs on Web.
- Can I use BigQuery ML for free?
- Yes. BigQuery ML 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 calling hosted language models from an application, generating images, audio and embeddings through one api, building agents and tool calling workflows on managed models. Of those, calling hosted language models from an application and generating images, audio and embeddings through one api are not what BigQuery ML is typically brought in for.
- What can OpenAI API do that BigQuery ML cannot?
- OpenAI API covers GPT models, DALL-E, Whisper, Embeddings. BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions.