Feyn AI Releases SQRL, a Text-to-SQL Model Family That Inspects the Database Before Writing a Query
Feyn Labs released SQRL, a text-to-SQL model family that inspects databases via read-only probes before generating queries. The flagship model outperforms Claude Opus on the BIRD benchmark.
- SQRL models use read-only probes to inspect databases before writing SQL queries.
- The SQRL-35B-A3B model achieves 70.6% accuracy on the BIRD Dev benchmark.
- Smaller 4B and 9B parameter versions are available for self-hosting.
- Performance claims suggest the model beats Claude Opus 4.6 on this specific benchmark.
Feyn Labs has introduced SQRL, a new family of text-to-SQL models designed to improve query accuracy by inspecting the database structure first. Unlike traditional models that generate SQL directly from prompts, SQRL uses read-only probes to understand the schema and data distribution before committing to a query.
The flagship model, SQRL-35B-A3B, reportedly achieved 70.6% execution accuracy on the BIRD Dev benchmark. This score places it slightly ahead of Claude Opus 4.6, indicating a significant step forward for specialized database interaction models.
In addition to the large 35B parameter model, Feyn Labs has released smaller, distilled versions with 4B and 9B parameters. These smaller checkpoints are designed to be self-hostable, giving developers the option to run high-performance text-to-SQL models on their own infrastructure.
Provides access to efficient, self-hostable text-to-SQL models that can be integrated into local applications.
Enables more accurate natural language data querying without relying solely on expensive external APIs.
Demonstrates progress in making complex database querying accessible through natural language.
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