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.

74
openai/gpt-5-nano
Average duration
26s
Average tokens
3542
Average cost
$0.00
50
20s
2947
opper_normalization_sample_01
50
50s
4911
opper_normalization_sample_02
100
15s
2222
opper_normalization_sample_03
0
20s
4147
opper_normalization_sample_04
50
18s
4112
opper_normalization_sample_05
50
2m 31s
7691
opper_normalization_sample_06
0
20s
2908
opper_normalization_sample_07
100
37s
8323
opper_normalization_sample_08
0
26s
6408
opper_normalization_sample_09
100
50s
7332
opper_normalization_sample_10
100
40s
1959
opper_normalization_sample_11
100
13s
1975
opper_normalization_sample_12
50
20s
2361
opper_normalization_sample_13
100
27s
5259
opper_normalization_sample_14
100
20s
2884
opper_normalization_sample_15
100
14s
1706
opper_normalization_sample_16
100
14s
1475
opper_normalization_sample_17
100
10s
1940
opper_normalization_sample_18
100
13s
1668
opper_normalization_sample_19
50
20s
4330
opper_normalization_sample_20
0
13s
1564
opper_normalization_sample_21
100
14s
2496
opper_normalization_sample_22
100
20s
3565
opper_normalization_sample_23
100
13s
2201
opper_normalization_sample_24
100
14s
2644
opper_normalization_sample_25
100
18s
3858
opper_normalization_sample_26
100
12s
2739
opper_normalization_sample_27