license: cc-by-nc-4.0
base_model:
- Qwen/Qwen2.5-Coder-32B
ExCoT
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:
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.
Both models significantly outperformed larger open-weight models, such as Mistral 123B, and even proprietary systems including GPT-4o and Claude 3.5 — achieving over 12 percentage points of improvement.
For more details about ExCoT and how to use it: