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.

85
gcp/gemini-2.0-flash
Average duration
9s
Average tokens
979
Average cost
$0.00
100
11s
987
opper_normalization_sample_01
50
10s
1137
opper_normalization_sample_02
100
11s
1164
opper_normalization_sample_03
100
11s
917
opper_normalization_sample_04
50
10s
1281
opper_normalization_sample_05
50
10s
1247
opper_normalization_sample_06
100
10s
1455
opper_normalization_sample_07
50
11s
1371
opper_normalization_sample_08
50
10s
1946
opper_normalization_sample_09
100
11s
494
opper_normalization_sample_10
100
10s
438
opper_normalization_sample_11
100
10s
646
opper_normalization_sample_12
100
10s
791
opper_normalization_sample_13
100
10s
846
opper_normalization_sample_14
100
11s
964
opper_normalization_sample_15
100
8s
626
opper_normalization_sample_16
100
8s
605
opper_normalization_sample_17
50
8s
612
opper_normalization_sample_18
100
8s
609
opper_normalization_sample_19
100
7s
1521
opper_normalization_sample_20
0
8s
576
opper_normalization_sample_21
100
7s
646
opper_normalization_sample_22
100
8s
1324
opper_normalization_sample_23
100
8s
1028
opper_normalization_sample_24
100
8s
1046
opper_normalization_sample_25
100
8s
1120
opper_normalization_sample_26
100
8s
1037
opper_normalization_sample_27