SQL

Natural language to SQL query generation evaluates text-to-query fidelity and schema reasoning. This task is particularly relevant for analytics chat assistants and simplified database interfaces where users need to query data using natural language. Models must understand both the intent behind the question and the structure of the underlying database schema.

92
cerebras/qwen-3-235b-a22b-instruct-2507
Average duration
5s
Average tokens
903
Average cost
$0.00
100
5s
625
opper_sql_sample_01
100
4s
666
opper_sql_sample_02
100
3s
661
opper_sql_sample_03
100
3s
650
opper_sql_sample_04
100
3s
697
opper_sql_sample_05
100
3s
721
opper_sql_sample_06
100
3s
625
opper_sql_sample_07
100
3s
636
opper_sql_sample_08
100
3s
639
opper_sql_sample_09
100
5s
677
opper_sql_sample_10
100
4s
843
opper_sql_sample_11
100
3s
939
opper_sql_sample_12
100
4s
894
opper_sql_sample_13
100
3s
921
opper_sql_sample_14
75
12s
942
opper_sql_sample_15
100
6s
984
opper_sql_sample_16
100
3s
922
opper_sql_sample_17
75
10s
1044
opper_sql_sample_18
50
10s
907
opper_sql_sample_19
100
4s
1002
opper_sql_sample_20
100
5s
1045
opper_sql_sample_21
100
5s
1099
opper_sql_sample_22
100
3s
1121
opper_sql_sample_23
50
10s
1131
opper_sql_sample_24
100
4s
1175
opper_sql_sample_25
100
5s
1127
opper_sql_sample_26
75
3s
1076
opper_sql_sample_27
75
5s
1200
opper_sql_sample_28
50
5s
1092
opper_sql_sample_29
100
4s
1042
opper_sql_sample_30