---
license: cc-by-nc-4.0
base_model:
- Qwen/Qwen2.5-Coder-32B
---

# Arctic Text2SQL: 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](https://bird-bench.github.io/), 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](https://huggingface.co./Snowflake/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](https://huggingface.co./Snowflake/Qwen-2.5-coder-Arctic-ExCoT-32B) achieved similarly strong gains.

* Both models significantly outperformed other well-known frontier general-purpose models, achieving over 10 points of improvement.

For more details about ExCoT and how to use it:

* ❄️ [Arctic Text2SQL: Introducing ExCoT for Execution-Guided Chain-of-Thought Optimization (blog)]()
* 📝 [ExCoT: Optimizing Reasoning for Text-to-SQL with Execution Feedback (arxiv)](https://arxiv.org/pdf/2503.19988)
* 🚀 [Getting started guide using ArcticTraining](https://github.com/snowflakedb/ArcticTraining/tree/main/projects/excot_dpo)

## Evaluation results

| Model                                 |  |              |
|--------------------------------------|----------------|--------------|
|                                      | BIRD Ex% Dev        | BIRD Ex% Test     |
| Arctic-ExCoT-70B (LLaMA 3.1 70B)      | **68.51** | 68.53    |
| Arctic-ExCoT-32B (Qwen-2.5-Coder 32B) | 68.25   | 68.19    |
| XiYanSQL-QwenCoder*                   | 67.01   | **69.03** |
| OpenAI GPT-4o                         | 54.04   | –        |
| OpenAI GPT-4                          | 46.35   | 54.89    |
| Anthropic Claude 3.5-Sonnet          | 50.13   | –        |
| Claude-2                              | 42.70   | 49.02    |
| OpenAI o1-mini                        | 52.41   | –        |
| OpenAI o3-mini                        | 53.72   | –        |
| Mistral-large-2407 (123B)             | 53.52   | 55.84    |
| DeepSeek-V2 (236B)                    | 56.13   | 56.68    |

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]](https://github.com/XGenerationLab/XiYanSQL-QwenCoder/issues/4)[[2]](https://modelscope.cn/models/XGenerationLab/XiYanSQL-QwenCoder-32B-2412/feedback/issueDetail/22708).