samsung SM-S928W
Geekbench ML Score
1316
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| User | SyderAkaris |
| Upload Date | July 13 2024 04:12 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S928W |
| Model ID | samsung SM-S928W |
| Motherboard | pineapple |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.40 GHz |
| Memory Information | |
|---|---|
| Size | 10.81 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
788
147.5 IPS |
|
|
Image Classification (F16)
|
100% |
695
130.0 IPS |
|
|
Image Classification (I8)
|
99% |
665
124.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
815
13.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
1047
17.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
1054
17.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
1079
1.31 IPS |
|
|
Pose Estimation (F16)
|
100% |
2657
3.22 IPS |
|
|
Pose Estimation (I8)
|
100% |
2664
3.23 IPS |
|
|
Object Detection (F32)
|
100% |
286
21.3 IPS |
|
|
Object Detection (F16)
|
100% |
431
32.2 IPS |
|
|
Object Detection (I8)
|
62% |
398
29.7 IPS |
|
|
Face Detection (F32)
|
100% |
2803
33.3 IPS |
|
|
Face Detection (F16)
|
97% |
2972
35.3 IPS |
|
|
Face Detection (I8)
|
86% |
2646
31.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
1885
14.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
4026
31.2 IPS |
|
|
Depth Estimation (I8)
|
95% |
4040
31.3 IPS |
|
|
Style Transfer (F32)
|
100% |
7232
9.51 IPS |
|
|
Style Transfer (F16)
|
100% |
11608
15.3 IPS |
|
|
Style Transfer (I8)
|
98% |
11625
15.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
560
20.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1144
40.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1279
45.7 IPS |
|
|
Text Classification (F32)
|
100% |
443
636.6 IPS |
|
|
Text Classification (F16)
|
100% |
438
629.0 IPS |
|
|
Text Classification (I8)
|
92% |
717
1.03 KIPS |
|
|
Machine Translation (F32)
|
100% |
717
13.2 IPS |
|
|
Machine Translation (F16)
|
100% |
708
13.0 IPS |
|
|
Machine Translation (I8)
|
64% |
821
15.1 IPS |
