UniQL - T-SQL: leaderboard

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

Metric: Execution accuracy (%) on the T-SQL 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 July 2027. 13 models tracked.

Top models

#ModelScoreOverall rank
1Claude Sonnet 4.556.26#250
2Gemini 2.5 Pro55.61#266
3GPT-5.1 Codex54.63#288
4GPT-5 Mini53.85#348
5Qwen 3 32B51.69#960
6DeepSeek V4 Flash51.43#258
7Qwen 3 8B48.57#1830
8Qwen 3 4B46.41#2281
9Llama 3 70B Instruct40.61#1676
10GPT-3.5 Turbo37.74#2753
11Qwen 3 1.7B32.66#5520
12Llama 3 8B Instruct21.12#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-t-sql · How It Works · Data refreshed daily, snapshot 2026-11-13.