Software · head to head
Cohere vs BigQuery ML
The short version
- Each has a real cost: Cohere aPI-only service with no self-hosted options for most users; BigQuery ML not available in BigQuery's Standard edition, so the cheapest tier cannot use it
- They diverge on capability: Cohere covers Generate, BigQuery ML covers SQL-based ML.
Where they differ
Only the attributes on which Cohere and BigQuery ML actually diverge.
| Attribute | Cohere | BigQuery ML |
|---|---|---|
| Platforms | Api, Cloud | Web |
| Founded | 2019 | 2008 |
Identical on both: starting price (Free), pricing model (usage-based), free tier (Yes), 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 Cohere
- Generate
- Embed
- Rerank
- Classify
- REST API
- SDKs
- Cloud deployment
- 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.
Cohere
- ai tools managementnot BigQuery ML
- Workflow automationnot BigQuery ML
- Reportingnot BigQuery ML
BigQuery ML
- Training models in SQL without exporting datanot Cohere
- Linear and logistic regression on warehouse datanot Cohere
- K-means clustering and matrix factorisation for recommendationsnot Cohere
- Time series forecasting with ARIMA_PLUSnot Cohere
- Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot Cohere
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Cohere
- API-only service with no self-hosted options for most users
- Trial tier severely limited at 1,000 calls per month
- Smaller context window compared to some competing APIs
- Less emphasis on safety and alignment compared to competing APIs
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
Cohere
Free- Free TrialFree
- Rate limited
- Evaluation
- Production$0.4/per-million-tokens
- Full access
- SLA
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 Cohere if
- You need generate.
- You want to start without paying.
- You work on Api, Cloud.
- You also want embed.
Choose BigQuery ML if
- You need sql-based ml.
- You want to start without paying.
- You also want automl tables.
Questions people ask
- Is Cohere or BigQuery ML better?
- Neither clearly leads. Cohere starts at Free and BigQuery ML at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Cohere or BigQuery ML?
- Cohere starts at Free and BigQuery ML at Free.
- Does Cohere or BigQuery ML run on more platforms?
- Cohere runs on Api, Cloud. BigQuery ML runs on Web.
- Can I use Cohere for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Cohere best used for?
- Cohere is most often used for ai tools management, workflow automation, reporting. Of those, ai tools management and workflow automation are not what BigQuery ML is typically brought in for.
- What can Cohere do that BigQuery ML cannot?
- Cohere covers Generate, Embed, Rerank, Classify. BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions.
Answered from the vendors’ own pages
Cohere: Does Cohere offer a free tier?
Yes. Cohere provides Trial API keys that allow 1,000 free API calls per month across all models and endpoints. Trial keys are rate-limited to 20 requests per minute for Chat endpoints and 5-10 requests per minute for other endpoints, and cannot be used for production or commercial purposes.
SourceCohere: What is the cost structure for production use?
Cohere uses pay-as-you-go pricing based on tokens consumed. Costs vary by model: Command costs from 0.15 to 2.50 USD per 1M input tokens, with output tokens priced higher. Embed models cost 0.10 USD per 1M input tokens. Production keys have monthly billing with invoices at month-end or when charges reach 250 USD.
SourceCohere: Can I self-host Cohere models?
No. Cohere operates as an API-only platform. However, enterprise customers can arrange dedicated or managed deployments through the Model Vault platform starting at 4.00 USD per hour with custom pricing for dedicated instances.
SourceCohere: What are the main differences between Cohere and Claude API?
Cohere excels in cost-effective NLP applications and retrieval-augmented generation (RAG) capabilities. Claude API emphasizes reasoning and safety with Constitutional AI training. Cohere's Command R+ offers similar performance to GPT-4 at 40-50 percent lower cost, while Claude focuses on factual accuracy and transparency.
Source