The use case: how Snowflake deploys Mistral
Snowflake uses Mistral Large and Codestral in Cortex Analyst, its AI assistant for structured data, to generate SQL from natural language questions and explain results conversationally. A multi-agent approach has several agents draft SQL and another synthesize the final query.
More reported results
Figures published in Mistral’s case study. They are not independently measured by usedby.
delivers approximately 14% higher accuracy than another competing text-to-SQL solution in the market
Cortex Analyst achieved ~90% or higher accuracy reliably across customer evaluations as well as in benchmark tests
In the customer’s words
With Mistral Large and Codestral, Snowflake is delivering cutting-edge text-to-sql capabilities for complex and nuanced enterprise data.Other AI tools used by Snowflake
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Go straight to the source
Based on Mistral’s published case study. We check the public evidence; the results are reported by the vendor.
mistral.ai- Source published
- Apr 24, 2026
- Last checked
- Oct 9, 2026
Open source capture What the story claims, and what we checked
What we compared with the page.
- The figure: 2xChecked
The figure is on the page; its label is our wording.
- The passage quoted aboveChecked
Copied word for word from the page, near the name of Snowflake.
- The publication dateChecked
Read from the page’s own metadata, never guessed.
- Snowflake uses MistralChecked
Confirmed line.
- The result itselfNot checked
We quote it; we did not measure it.
Based on internal evaluation sets, using Mistral Large and Codestral, Cortex Analyst is consistently close to 2x more accurate than single-shot SQL generation from state-of-the-art LLMs and delivers approximately 14% higher accuracy than another competing text-to-SQL solution in the market.