HONOR PTP-AN10
Geekbench ML Score
2020
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | November 20 2024 02:07 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | HONOR PTP-AN10 |
| Model ID | HONOR PTP-AN10 |
| Motherboard | PTP |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm SM8750 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.32 GHz |
| Memory Information | |
|---|---|
| Size | 10.93 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1061
198.5 IPS |
|
|
Image Classification (F16)
|
100% |
1289
241.2 IPS |
|
|
Image Classification (I8)
|
97% |
1757
328.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
1607
26.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1568
26.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
1861
31.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
2031
2.46 IPS |
|
|
Pose Estimation (F16)
|
100% |
1995
2.42 IPS |
|
|
Pose Estimation (I8)
|
100% |
8555
10.4 IPS |
|
|
Object Detection (F32)
|
100% |
1154
86.2 IPS |
|
|
Object Detection (F16)
|
100% |
1167
87.1 IPS |
|
|
Object Detection (I8)
|
61% |
2172
162.2 IPS |
|
|
Face Detection (F32)
|
100% |
2255
26.8 IPS |
|
|
Face Detection (F16)
|
100% |
2276
27.1 IPS |
|
|
Face Detection (I8)
|
86% |
4379
52.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
2083
16.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
2087
16.2 IPS |
|
|
Depth Estimation (I8)
|
95% |
4418
34.3 IPS |
|
|
Style Transfer (F32)
|
100% |
3198
4.21 IPS |
|
|
Style Transfer (F16)
|
100% |
3231
4.25 IPS |
|
|
Style Transfer (I8)
|
98% |
9747
12.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1314
46.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1351
48.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
4111
146.8 IPS |
|
|
Text Classification (F32)
|
100% |
1083
1.56 KIPS |
|
|
Text Classification (F16)
|
100% |
1146
1.65 KIPS |
|
|
Text Classification (I8)
|
92% |
862
1.24 KIPS |
|
|
Machine Translation (F32)
|
100% |
1920
35.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1828
33.6 IPS |
|
|
Machine Translation (I8)
|
64% |
1074
19.8 IPS |
