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BigQuery adds daily token quotas for generative AI functions

Google Cloud made daily token quotas generally available for BigQuery functions that invoke language models from SQL. AI.GENERATE, AI.GENERATE_TEXT, AI.CLASSIFY, AI.IF and related generation functions are covered. Administrators can set project and per-user ceilings to contain token use in large analytical queries.

Newsverum · Source brief1 min read

Event / data period: 2026-10-14

Published: · Updated:

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Project defaults are 200 billion input and 20 billion output tokens per day; per-user defaults are 150 billion input and 15 billion output. Use aggregates across regions, and reasoning tokens count as output. Embedding functions are excluded. Administrators can change the limits in the console without a support case.

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BigQuery adds daily token quotas for generative AI functions

Google Cloud made daily token quotas generally available for BigQuery functions that invoke language models from SQL. AI.GENERATE, AI.GENERATE_TEXT, AI.CLASSIFY, AI.IF and related generation functions are covered. Administrators can set project and per-user ceilings to contain token use in large analytical queries. Project defaults are 200 billion input and 20 billion output tokens per day; per-user defaults are 150 billion input and 15 billion output. Use aggregates across regions, and reasoning tokens count as output. Embedding functions are excluded. Administrators can change the limits in the console without a support case.

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    BigQuery adds daily token quotas for generative AI functions

    Google Cloud made daily token quotas generally available for BigQuery functions that invoke language models from SQL. AI.GENERATE, AI.GENERATE_TEXT, AI.CLASSIFY, AI.IF and related generation functions are covered. Administrators can set project and per-user ceilings to contain token use in large analytical queries. Project defaults are 200 billion input and 20 billion output tokens per day; per-user defaults are 150 billion input and 15 billion output. Use aggregates across regions, and reasoning tokens count as output. Embedding functions are excluded. Administrators can change the limits in the console without a support case.

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Alteryx and BigQuery bring live queries to unstructured data

Alteryx and Google Cloud published an architecture example combining Live Query and BigQuery for unstructured-document workflows. Invoice PDFs remain in Cloud Storage; Alteryx authors the flow in a browser, while SQL pushdown runs transformations and reconciliation in BigQuery. Gemini AI.GENERATE extracts invoice fields in the worked example.

Google Cloud and Alteryx1 min read Data included