samsung SM-S928U1
Geekbench ML Score
1095
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 03:20 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S928U1 |
| Model ID | samsung SM-S928U1 |
| 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% |
384
71.9 IPS |
|
|
Image Classification (F16)
|
100% |
685
128.1 IPS |
|
|
Image Classification (I8)
|
99% |
655
122.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
795
13.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1099
18.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
1051
17.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
907
1.10 IPS |
|
|
Pose Estimation (F16)
|
100% |
1878
2.27 IPS |
|
|
Pose Estimation (I8)
|
100% |
1907
2.31 IPS |
|
|
Object Detection (F32)
|
100% |
262
19.5 IPS |
|
|
Object Detection (F16)
|
100% |
431
32.2 IPS |
|
|
Object Detection (I8)
|
62% |
418
31.2 IPS |
|
|
Face Detection (F32)
|
100% |
2146
25.5 IPS |
|
|
Face Detection (F16)
|
97% |
2959
35.2 IPS |
|
|
Face Detection (I8)
|
86% |
1930
22.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
1447
11.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
2814
21.8 IPS |
|
|
Depth Estimation (I8)
|
95% |
2878
22.3 IPS |
|
|
Style Transfer (F32)
|
100% |
4850
6.38 IPS |
|
|
Style Transfer (F16)
|
100% |
8050
10.6 IPS |
|
|
Style Transfer (I8)
|
98% |
8024
10.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
430
15.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1189
42.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1108
39.6 IPS |
|
|
Text Classification (F32)
|
100% |
368
528.8 IPS |
|
|
Text Classification (F16)
|
100% |
373
536.1 IPS |
|
|
Text Classification (I8)
|
92% |
602
865.8 IPS |
|
|
Machine Translation (F32)
|
100% |
641
11.8 IPS |
|
|
Machine Translation (F16)
|
100% |
642
11.8 IPS |
|
|
Machine Translation (I8)
|
64% |
728
13.4 IPS |
