Data Normalization

Data processing and normalization tasks evaluate structured output from messy prose and different structures. This capability is essential for catalogue and product pipelines where data needs to be extracted from unstructured text and formatted consistently. Models must understand the desired output format and extract relevant information accurately.

78
gcp/gemini-2.0-flash-lite
Average duration
9s
Average tokens
981
Average cost
$0.00
100
10s
1000
opper_normalization_sample_01
50
11s
1149
opper_normalization_sample_02
100
11s
1187
opper_normalization_sample_03
50
11s
935
opper_normalization_sample_04
50
10s
1298
opper_normalization_sample_05
50
10s
1243
opper_normalization_sample_06
100
10s
1440
opper_normalization_sample_07
50
10s
1451
opper_normalization_sample_08
50
11s
1799
opper_normalization_sample_09
0
11s
846
opper_normalization_sample_10
100
10s
447
opper_normalization_sample_11
100
10s
647
opper_normalization_sample_12
100
10s
777
opper_normalization_sample_13
100
10s
839
opper_normalization_sample_14
100
11s
1011
opper_normalization_sample_15
50
8s
622
opper_normalization_sample_16
100
8s
590
opper_normalization_sample_17
100
8s
648
opper_normalization_sample_18
100
8s
592
opper_normalization_sample_19
50
7s
1554
opper_normalization_sample_20
100
7s
604
opper_normalization_sample_21
100
8s
722
opper_normalization_sample_22
100
8s
921
opper_normalization_sample_23
100
8s
1132
opper_normalization_sample_24
100
7s
887
opper_normalization_sample_25
100
8s
1070
opper_normalization_sample_26
0
7s
1088
opper_normalization_sample_27