UniQL - DuckDB: leaderboard
Metric: Execution accuracy (%) on the DuckDB dialect of UniQL (1,534 BIRD development-set questions with human-verified SQL in 16 aligned dialects): given the target dialect, schema and question, the model writes one query whose execution result must match the gold result; inference-only, one run; higher is better. Source: arxiv.org. Saturation forecast: Around 2028. 13 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | Gemini 2.5 Pro | 56.19 |
| 2 | Claude Sonnet 4.5 | 55.28 |
| 3 | GPT-5.1 Codex | 52.93 |
| 4 | GPT-5 Mini | 52.74 |
| 5 | Qwen 3 32B | 49.93 |
| 6 | DeepSeek V4 Flash | 49.02 |
| 7 | Qwen 3 8B | 47 |
| 8 | Qwen 3 4B | 44.26 |
| 9 | Llama 3 70B Instruct | 41.72 |
| 10 | GPT-3.5 Turbo | 37.09 |
| 11 | Qwen 3 1.7B | 35.27 |
| 12 | Llama 3 8B Instruct | 22.29 |
Interactive version: theaggregate.ai/benchmark?slug=uniql-duckdb · How It Works · Data refreshed daily, snapshot 2026-09-29.