TECNO TECNO CK8n
Geekbench ML Score
496
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 12 2024 07:01 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | TECNO TECNO CK8n |
| Model ID | TECNO TECNO CK8n |
| Motherboard | TECNO-CK8n |
| CPU Information | |
|---|---|
| Name | ARM MT6893Z_T/CZA |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 3 Cores @ 2.60 GHz |
| Cluster 3 | 1 Core @ 3.00 GHz |
| Memory Information | |
|---|---|
| Size | 7.32 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
233
43.6 IPS |
|
|
Image Classification (F16)
|
100% |
236
44.2 IPS |
|
|
Image Classification (I8)
|
97% |
381
71.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
326
5.45 IPS |
|
|
Image Segmentation (F16)
|
100% |
344
5.74 IPS |
|
|
Image Segmentation (I8)
|
98% |
523
8.73 IPS |
|
|
Pose Estimation (F32)
|
100% |
478
0.58 IPS |
|
|
Pose Estimation (F16)
|
100% |
434
0.53 IPS |
|
|
Pose Estimation (I8)
|
100% |
2315
2.80 IPS |
|
|
Object Detection (F32)
|
100% |
259
19.4 IPS |
|
|
Object Detection (F16)
|
100% |
240
17.9 IPS |
|
|
Object Detection (I8)
|
61% |
439
32.8 IPS |
|
|
Face Detection (F32)
|
100% |
562
6.68 IPS |
|
|
Face Detection (F16)
|
100% |
540
6.42 IPS |
|
|
Face Detection (I8)
|
86% |
1074
12.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
520
4.03 IPS |
|
|
Depth Estimation (F16)
|
100% |
506
3.93 IPS |
|
|
Depth Estimation (I8)
|
95% |
937
7.26 IPS |
|
|
Style Transfer (F32)
|
100% |
1008
1.33 IPS |
|
|
Style Transfer (F16)
|
100% |
980
1.29 IPS |
|
|
Style Transfer (I8)
|
98% |
2556
3.36 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
334
11.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
333
11.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1003
35.8 IPS |
|
|
Text Classification (F32)
|
100% |
341
489.6 IPS |
|
|
Text Classification (F16)
|
100% |
312
448.4 IPS |
|
|
Text Classification (I8)
|
92% |
365
524.6 IPS |
|
|
Machine Translation (F32)
|
100% |
455
8.38 IPS |
|
|
Machine Translation (F16)
|
100% |
464
8.53 IPS |
|
|
Machine Translation (I8)
|
64% |
250
4.60 IPS |
