๐๐ผ๐ผ๐ด๐น๐ฒ ๐๐ฒ๐บ๐ถ๐ป๐ถ-๐ฆ๐ค๐๐ฎ ๐๐ฒ๐ฎ๐๐ ๐๐ฃ๐ง-๐ฑ.๐ฑ ๐ข๐ป ๐ฆ๐ค๐ ๐๐ฒ๐ป๐ฐ๐ต๐บ๐ฎ๐ฟ๐ธ๐
Google Research shows a new lead in the AI coding race.
Their new system, Gemini-SQL2, hit 80.04% on the BIRD benchmark. This benchmark tests how well AI turns plain English into SQL code for databases.
The results show a large gap between Google and its rivals:
โข Gemini-SQL2: 80.04% โข GPT-5.5-xhigh: 72.8% โข Claude Opus 4.6: 70.9%
Gemini-SQL2 uses the Gemini 3.1 Pro model. It beats GPT-5.5 by 7 points. It beats Claude by 9 points. This gap is much larger than typical differences seen in other AI benchmarks.
Why this matters for your business:
Accuracy is the biggest problem with AI data tools. One wrong line of code produces a wrong answer. Most general models struggle with complex database logic. Google's specialized approach shows better results for structured data tasks.
If Google adds this to BigQuery or Google Cloud, it will change how you interact with data. You will query production databases using natural language instead of writing manual code.
Google has not released a research paper or a public version yet. We do not know the exact technical details. We only know the performance numbers.
Keep an eye on whether Google publishes the research or ships this feature to Google Cloud soon.
Source: https://dev.to/gentic_news/google-gemini-sql2-hits-8004-on-bird-beating-gpt-55-by-7-points-423f
Optional learning community: https://t.me/GyaanSetuAi