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.

88
mistral/pixtral-large-latest-eu
Average duration
9s
Average tokens
1054
Average cost
$0.00
100
6s
681
opper_sql_sample_01
100
8s
721
opper_sql_sample_02
100
4s
710
opper_sql_sample_03
100
11s
686
opper_sql_sample_04
100
37s
755
opper_sql_sample_05
100
4s
806
opper_sql_sample_06
100
3s
687
opper_sql_sample_07
100
5s
707
opper_sql_sample_08
100
5s
698
opper_sql_sample_09
100
4s
766
opper_sql_sample_10
100
7s
980
opper_sql_sample_11
100
4s
1053
opper_sql_sample_12
100
8s
1081
opper_sql_sample_13
100
7s
1086
opper_sql_sample_14
100
10s
1091
opper_sql_sample_15
50
4s
1130
opper_sql_sample_16
100
4s
1101
opper_sql_sample_17
75
6s
1304
opper_sql_sample_18
50
1m 7s
1097
opper_sql_sample_19
100
7s
1229
opper_sql_sample_20
100
4s
1253
opper_sql_sample_21
75
5s
1339
opper_sql_sample_22
100
5s
1376
opper_sql_sample_23
75
4s
1346
opper_sql_sample_24
75
5s
1380
opper_sql_sample_25
75
5s
1303
opper_sql_sample_26
50
4s
1272
opper_sql_sample_27
75
5s
1417
opper_sql_sample_28
50
6s
1338
opper_sql_sample_29
100
4s
1224
opper_sql_sample_30