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.

59
mistral/mistral-small-eu
Average duration
11s
Average tokens
1085
Average cost
$0.00
50
55s
1140
opper_normalization_sample_01
0
5s
1224
opper_normalization_sample_02
100
5s
1379
opper_normalization_sample_03
50
4s
1032
opper_normalization_sample_04
50
6s
1455
opper_normalization_sample_05
50
6s
1388
opper_normalization_sample_06
0
6s
1673
opper_normalization_sample_07
0
14s
1605
opper_normalization_sample_08
0
14s
2011
opper_normalization_sample_09
50
5s
541
opper_normalization_sample_10
0
4s
464
opper_normalization_sample_11
100
4s
704
opper_normalization_sample_12
100
5s
859
opper_normalization_sample_13
100
5s
971
opper_normalization_sample_14
100
27s
1126
opper_normalization_sample_15
50
4s
689
opper_normalization_sample_16
100
4s
642
opper_normalization_sample_17
100
5s
659
opper_normalization_sample_18
100
24s
656
opper_normalization_sample_19
100
6s
1684
opper_normalization_sample_20
50
4s
635
opper_normalization_sample_21
0
4s
763
opper_normalization_sample_22
100
6s
1219
opper_normalization_sample_23
100
6s
1241
opper_normalization_sample_24
100
54s
1046
opper_normalization_sample_25
50
5s
1216
opper_normalization_sample_26
0
5s
1262
opper_normalization_sample_27