Snowflake’s AI research team introduces ExCoT, the first model in the Arctic Text2SQL family. ExCoT is a novel framework that combines CoT prompting with SQL execution-based DPO, using execution results — not human preferences — as the feedback signal. This enables scalable, high-quality model optimization without requiring expensive human annotations.
Based on our internal testing, ExCoT delivered state-of-the-art results on the
BIRD-test benchmark, achieving best-in-class performance in the single-model, single-inference category using only public datasets (BIRD and Spider) and no additional Text2SQL data:
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Llama-3.1-Arctic-ExCoT-70B improved execution accuracy on the BIRD-dev set from the base model’s 57.37% to 68.51%.
Qwen-2.5-coder-Arctic-ExCoT-32B achieved similarly strong gains.
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Both models significantly outperformed other well-known frontier general-purpose models, achieving over 10 points of improvement.
Top Single-Model, Single-Inference Results on the BIRD Leaderboard (as of March 25, 2025). *XiYanSQL-QwenCoder: there are some challenges to reproduce the numbers
[1][2].
