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
fireworks/qwen3-coder-480b-a35b-instruct
Average duration
5s
Average tokens
896
Average cost
$0.00
100
4s
620
opper_sql_sample_01
100
4s
651
opper_sql_sample_02
100
4s
638
opper_sql_sample_03
100
3s
620
opper_sql_sample_04
100
4s
693
opper_sql_sample_05
100
4s
711
opper_sql_sample_06
100
3s
624
opper_sql_sample_07
100
3s
621
opper_sql_sample_08
100
3s
622
opper_sql_sample_09
100
4s
669
opper_sql_sample_10
100
4s
827
opper_sql_sample_11
100
5s
895
opper_sql_sample_12
100
5s
908
opper_sql_sample_13
100
7s
923
opper_sql_sample_14
75
5s
916
opper_sql_sample_15
100
7s
974
opper_sql_sample_16
100
4s
913
opper_sql_sample_17
50
5s
1032
opper_sql_sample_18
50
7s
905
opper_sql_sample_19
100
5s
992
opper_sql_sample_20
100
7s
1040
opper_sql_sample_21
100
4s
1105
opper_sql_sample_22
100
5s
1129
opper_sql_sample_23
75
7s
1182
opper_sql_sample_24
75
6s
1154
opper_sql_sample_25
75
4s
1062
opper_sql_sample_26
0
6s
1093
opper_sql_sample_27
75
5s
1210
opper_sql_sample_28
100
5s
1098
opper_sql_sample_29
100
6s
1039
opper_sql_sample_30