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.

78
cerebras/qwen-3-235b-a22b-instruct-2507
Average duration
3s
Average tokens
1063
Average cost
$0.00
50
4s
1061
opper_normalization_sample_01
50
4s
1277
opper_normalization_sample_02
100
3s
1327
opper_normalization_sample_03
50
4s
964
opper_normalization_sample_04
50
3s
1309
opper_normalization_sample_05
50
3s
1268
opper_normalization_sample_06
0
5s
2578
opper_normalization_sample_07
100
3s
1440
opper_normalization_sample_08
50
3s
1886
opper_normalization_sample_09
100
3s
527
opper_normalization_sample_10
100
4s
473
opper_normalization_sample_11
100
3s
624
opper_normalization_sample_12
100
3s
738
opper_normalization_sample_13
100
4s
813
opper_normalization_sample_14
100
3s
893
opper_normalization_sample_15
100
3s
662
opper_normalization_sample_16
50
3s
640
opper_normalization_sample_17
50
3s
673
opper_normalization_sample_18
100
3s
641
opper_normalization_sample_19
50
3s
1554
opper_normalization_sample_20
50
3s
697
opper_normalization_sample_21
100
3s
789
opper_normalization_sample_22
100
5s
1142
opper_normalization_sample_23
100
5s
1349
opper_normalization_sample_24
100
3s
1212
opper_normalization_sample_25
100
3s
1096
opper_normalization_sample_26
100
3s
1065
opper_normalization_sample_27