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.

82
cerebras/qwen-3-32b
Average duration
5s
Average tokens
2479
Average cost
$0.00
100
4s
2001
opper_normalization_sample_01
0
7s
5134
opper_normalization_sample_02
100
4s
1738
opper_normalization_sample_03
50
8s
2372
opper_normalization_sample_04
50
3s
1951
opper_normalization_sample_05
50
8s
7429
opper_normalization_sample_06
100
4s
1909
opper_normalization_sample_07
50
4s
3052
opper_normalization_sample_08
50
4s
2948
opper_normalization_sample_09
50
11s
9899
opper_normalization_sample_10
100
8s
6482
opper_normalization_sample_11
100
9s
909
opper_normalization_sample_12
100
5s
1054
opper_normalization_sample_13
100
7s
1875
opper_normalization_sample_14
100
4s
1204
opper_normalization_sample_15
100
3s
894
opper_normalization_sample_16
100
3s
1565
opper_normalization_sample_17
100
4s
929
opper_normalization_sample_18
100
3s
879
opper_normalization_sample_19
100
3s
2026
opper_normalization_sample_20
0
3s
1013
opper_normalization_sample_21
100
3s
1130
opper_normalization_sample_22
100
3s
1534
opper_normalization_sample_23
100
3s
1627
opper_normalization_sample_24
100
3s
1516
opper_normalization_sample_25
100
3s
2242
opper_normalization_sample_26
100
3s
1619
opper_normalization_sample_27