TECNO TECNO AD11
Geekbench ML Score
548
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 18 2024 08:16 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | TECNO TECNO AD11 |
| Model ID | TECNO TECNO AD11 |
| Motherboard | TECNO-AD11 |
| 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 | 7.35 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
281
52.6 IPS |
|
|
Image Classification (F16)
|
100% |
282
52.7 IPS |
|
|
Image Classification (I8)
|
97% |
502
94.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
352
5.87 IPS |
|
|
Image Segmentation (F16)
|
100% |
350
5.84 IPS |
|
|
Image Segmentation (I8)
|
98% |
487
8.13 IPS |
|
|
Pose Estimation (F32)
|
100% |
597
0.72 IPS |
|
|
Pose Estimation (F16)
|
100% |
545
0.66 IPS |
|
|
Pose Estimation (I8)
|
100% |
2338
2.83 IPS |
|
|
Object Detection (F32)
|
100% |
285
21.3 IPS |
|
|
Object Detection (F16)
|
100% |
286
21.4 IPS |
|
|
Object Detection (I8)
|
61% |
507
37.9 IPS |
|
|
Face Detection (F32)
|
100% |
620
7.37 IPS |
|
|
Face Detection (F16)
|
100% |
603
7.17 IPS |
|
|
Face Detection (I8)
|
86% |
1230
14.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
620
4.80 IPS |
|
|
Depth Estimation (F16)
|
100% |
602
4.67 IPS |
|
|
Depth Estimation (I8)
|
95% |
999
7.74 IPS |
|
|
Style Transfer (F32)
|
100% |
1140
1.50 IPS |
|
|
Style Transfer (F16)
|
100% |
1100
1.45 IPS |
|
|
Style Transfer (I8)
|
98% |
2639
3.47 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
360
12.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
364
13.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1056
37.7 IPS |
|
|
Text Classification (F32)
|
100% |
334
479.7 IPS |
|
|
Text Classification (F16)
|
100% |
335
481.5 IPS |
|
|
Text Classification (I8)
|
92% |
313
450.0 IPS |
|
|
Machine Translation (F32)
|
100% |
554
10.2 IPS |
|
|
Machine Translation (F16)
|
100% |
569
10.5 IPS |
|
|
Machine Translation (I8)
|
64% |
233
4.29 IPS |
