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
mistral/pixtral-large-latest-eu
Average duration
7s
Average tokens
1104
Average cost
$0.00
100
6s
1123
opper_normalization_sample_01
0
6s
1328
opper_normalization_sample_02
100
6s
1357
opper_normalization_sample_03
0
4s
1114
opper_normalization_sample_04
50
5s
1468
opper_normalization_sample_05
50
6s
1395
opper_normalization_sample_06
100
6s
1771
opper_normalization_sample_07
50
38s
1562
opper_normalization_sample_08
50
10s
2006
opper_normalization_sample_09
50
5s
554
opper_normalization_sample_10
100
3s
469
opper_normalization_sample_11
100
4s
767
opper_normalization_sample_12
100
4s
902
opper_normalization_sample_13
100
4s
994
opper_normalization_sample_14
50
4s
1146
opper_normalization_sample_15
100
4s
707
opper_normalization_sample_16
100
4s
678
opper_normalization_sample_17
100
5s
711
opper_normalization_sample_18
100
4s
685
opper_normalization_sample_19
100
6s
1667
opper_normalization_sample_20
50
4s
665
opper_normalization_sample_21
100
4s
739
opper_normalization_sample_22
100
6s
1254
opper_normalization_sample_23
100
4s
1147
opper_normalization_sample_24
100
5s
1099
opper_normalization_sample_25
50
35s
1300
opper_normalization_sample_26
100
4s
1211
opper_normalization_sample_27