TECNO TECNO CK8n
Geekbench ML Score
473
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 09 2024 09:56 AM |
| Views | 2 |
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% |
240
44.8 IPS |
|
|
Image Classification (F16)
|
100% |
225
42.1 IPS |
|
|
Image Classification (I8)
|
97% |
381
71.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
341
5.69 IPS |
|
|
Image Segmentation (F16)
|
100% |
338
5.65 IPS |
|
|
Image Segmentation (I8)
|
98% |
416
6.95 IPS |
|
|
Pose Estimation (F32)
|
100% |
434
0.53 IPS |
|
|
Pose Estimation (F16)
|
100% |
411
0.50 IPS |
|
|
Pose Estimation (I8)
|
100% |
2389
2.89 IPS |
|
|
Object Detection (F32)
|
100% |
242
18.1 IPS |
|
|
Object Detection (F16)
|
100% |
241
18.0 IPS |
|
|
Object Detection (I8)
|
61% |
462
34.5 IPS |
|
|
Face Detection (F32)
|
100% |
552
6.57 IPS |
|
|
Face Detection (F16)
|
100% |
541
6.44 IPS |
|
|
Face Detection (I8)
|
86% |
1082
12.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
484
3.75 IPS |
|
|
Depth Estimation (F16)
|
100% |
499
3.87 IPS |
|
|
Depth Estimation (I8)
|
95% |
1076
8.35 IPS |
|
|
Style Transfer (F32)
|
100% |
932
1.23 IPS |
|
|
Style Transfer (F16)
|
100% |
904
1.19 IPS |
|
|
Style Transfer (I8)
|
98% |
2363
3.11 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
291
10.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
301
10.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
971
34.7 IPS |
|
|
Text Classification (F32)
|
100% |
286
411.0 IPS |
|
|
Text Classification (F16)
|
100% |
280
402.1 IPS |
|
|
Text Classification (I8)
|
92% |
312
448.5 IPS |
|
|
Machine Translation (F32)
|
100% |
455
8.37 IPS |
|
|
Machine Translation (F16)
|
100% |
444
8.17 IPS |
|
|
Machine Translation (I8)
|
64% |
230
4.23 IPS |
