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.

80
anthropic/claude-opus-4
Average duration
17s
Average tokens
1230
Average cost
$0.00
100
20s
1265
opper_normalization_sample_01
100
18s
1391
opper_normalization_sample_02
100
18s
1488
opper_normalization_sample_03
100
18s
1214
opper_normalization_sample_04
50
18s
1526
opper_normalization_sample_05
50
18s
1504
opper_normalization_sample_06
50
20s
1824
opper_normalization_sample_07
50
29s
1637
opper_normalization_sample_08
50
34s
2109
opper_normalization_sample_09
0
20s
1000
opper_normalization_sample_10
100
16s
581
opper_normalization_sample_11
100
18s
862
opper_normalization_sample_12
0
18s
932
opper_normalization_sample_13
100
16s
1138
opper_normalization_sample_14
100
18s
1178
opper_normalization_sample_15
100
13s
787
opper_normalization_sample_16
100
13s
722
opper_normalization_sample_17
100
8s
740
opper_normalization_sample_18
100
12s
774
opper_normalization_sample_19
100
14s
1925
opper_normalization_sample_20
0
9s
729
opper_normalization_sample_21
100
11s
932
opper_normalization_sample_22
100
21s
1531
opper_normalization_sample_23
100
12s
1315
opper_normalization_sample_24
100
16s
1363
opper_normalization_sample_25
100
12s
1321
opper_normalization_sample_26
100
14s
1426
opper_normalization_sample_27