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.

89
gcp/gemini-flash-latest
Average duration
7s
Average tokens
2084
Average cost
$0.00
100
7s
2054
opper_normalization_sample_01
50
12s
2976
opper_normalization_sample_02
100
6s
2057
opper_normalization_sample_03
100
7s
1815
opper_normalization_sample_04
100
7s
2195
opper_normalization_sample_05
50
9s
2771
opper_normalization_sample_06
100
7s
2362
opper_normalization_sample_07
50
16s
3943
opper_normalization_sample_08
50
15s
3927
opper_normalization_sample_09
100
13s
2670
opper_normalization_sample_10
100
4s
963
opper_normalization_sample_11
100
6s
1762
opper_normalization_sample_12
100
6s
1681
opper_normalization_sample_13
100
9s
2242
opper_normalization_sample_14
100
8s
2346
opper_normalization_sample_15
100
4s
1234
opper_normalization_sample_16
100
5s
1299
opper_normalization_sample_17
100
4s
1104
opper_normalization_sample_18
100
4s
1076
opper_normalization_sample_19
100
7s
2896
opper_normalization_sample_20
0
4s
1044
opper_normalization_sample_21
100
7s
1703
opper_normalization_sample_22
100
8s
2280
opper_normalization_sample_23
100
7s
2167
opper_normalization_sample_24
100
6s
1944
opper_normalization_sample_25
100
6s
1874
opper_normalization_sample_26
100
6s
1884
opper_normalization_sample_27