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.

89
cerebras/qwen-3-32b
Average duration
6s
Average tokens
1742
Average cost
$0.00
100
8s
1248
opper_sql_sample_01
100
9s
1118
opper_sql_sample_02
100
5s
939
opper_sql_sample_03
100
5s
1794
opper_sql_sample_04
100
11s
1116
opper_sql_sample_05
100
3s
1293
opper_sql_sample_06
100
3s
967
opper_sql_sample_07
100
4s
842
opper_sql_sample_08
100
3s
869
opper_sql_sample_09
100
5s
1276
opper_sql_sample_10
100
3s
1007
opper_sql_sample_11
75
2s
1128
opper_sql_sample_12
100
3s
1397
opper_sql_sample_13
100
4s
1244
opper_sql_sample_14
75
9s
1856
opper_sql_sample_15
100
5s
2550
opper_sql_sample_16
100
8s
1524
opper_sql_sample_17
50
12s
3319
opper_sql_sample_18
100
5s
2544
opper_sql_sample_19
100
4s
2095
opper_sql_sample_20
100
10s
1349
opper_sql_sample_21
75
4s
2177
opper_sql_sample_22
100
6s
1978
opper_sql_sample_23
75
7s
1776
opper_sql_sample_24
100
6s
2955
opper_sql_sample_25
100
8s
1863
opper_sql_sample_26
50
6s
2347
opper_sql_sample_27
75
5s
3444
opper_sql_sample_28
0
4s
2745
opper_sql_sample_29
100
4s
1493
opper_sql_sample_30