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.

72
mistral/mistral-large-eu
Average duration
13s
Average tokens
1423
Average cost
$0.00
100
19s
2319
opper_normalization_sample_01
0
18s
1643
opper_normalization_sample_02
100
8s
1375
opper_normalization_sample_03
50
13s
1171
opper_normalization_sample_04
50
25s
2791
opper_normalization_sample_05
50
8s
1316
opper_normalization_sample_06
0
12s
1817
opper_normalization_sample_07
50
21s
1773
opper_normalization_sample_08
50
22s
2155
opper_normalization_sample_09
50
20s
1780
opper_normalization_sample_10
100
7s
519
opper_normalization_sample_11
100
7s
656
opper_normalization_sample_12
0
9s
958
opper_normalization_sample_13
100
37s
3251
opper_normalization_sample_14
50
8s
1040
opper_normalization_sample_15
100
8s
797
opper_normalization_sample_16
100
7s
722
opper_normalization_sample_17
100
7s
733
opper_normalization_sample_18
50
7s
734
opper_normalization_sample_19
100
26s
3058
opper_normalization_sample_20
50
9s
762
opper_normalization_sample_21
100
9s
852
opper_normalization_sample_22
100
11s
1265
opper_normalization_sample_23
100
9s
1231
opper_normalization_sample_24
100
9s
1139
opper_normalization_sample_25
100
11s
1289
opper_normalization_sample_26
100
10s
1278
opper_normalization_sample_27