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
gcp/gemini-flash-lite-latest
Average duration
2s
Average tokens
1273
Average cost
$0.00
100
3s
1214
opper_normalization_sample_01
0
3s
1643
opper_normalization_sample_02
100
3s
1556
opper_normalization_sample_03
100
3s
1404
opper_normalization_sample_04
0
2s
1514
opper_normalization_sample_05
0
3s
1675
opper_normalization_sample_06
100
3s
1836
opper_normalization_sample_07
100
3s
1616
opper_normalization_sample_08
50
4s
2089
opper_normalization_sample_09
100
2s
673
opper_normalization_sample_10
100
2s
586
opper_normalization_sample_11
100
2s
822
opper_normalization_sample_12
100
2s
1015
opper_normalization_sample_13
100
2s
1051
opper_normalization_sample_14
100
2s
1252
opper_normalization_sample_15
100
2s
805
opper_normalization_sample_16
100
2s
777
opper_normalization_sample_17
100
2s
802
opper_normalization_sample_18
100
2s
775
opper_normalization_sample_19
100
2s
2224
opper_normalization_sample_20
0
2s
799
opper_normalization_sample_21
0
2s
970
opper_normalization_sample_22
100
3s
1569
opper_normalization_sample_23
100
2s
1449
opper_normalization_sample_24
100
2s
1561
opper_normalization_sample_25
100
2s
1339
opper_normalization_sample_26
100
2s
1346
opper_normalization_sample_27