UniQL - DuckDB: leaderboard

Execution accuracy on the DuckDB dialect of UniQL (2026), which ports the 1,534 BIRD development questions to 16 SQL dialects: the percent of questions whose generated DuckDB query returns the gold result. Higher is better.

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 November 2027. 13 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 2.5 Pro56.19#266
2Claude Sonnet 4.555.28#250
3GPT-5.1 Codex52.93#288
4GPT-5 Mini52.74#348
5Qwen 3 32B49.93#960
6DeepSeek V4 Flash49.02#258
7Qwen 3 8B47#1830
8Qwen 3 4B44.26#2281
9Llama 3 70B Instruct41.72#1676
10GPT-3.5 Turbo37.09#2753
11Qwen 3 1.7B35.27#5520
12Llama 3 8B Instruct22.29#4612

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=uniql-duckdb · How It Works · Data refreshed daily, snapshot 2026-11-13.