samsung SM-S928U
Geekbench ML Score
1295
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 23 2024 04:09 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S928U |
| Model ID | samsung SM-S928U |
| 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
612
114.6 IPS |
|
|
Image Classification (F16)
|
100% |
618
115.7 IPS |
|
|
Image Classification (I8)
|
97% |
1113
208.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
825
13.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
810
13.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
1037
17.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
1541
1.87 IPS |
|
|
Pose Estimation (F16)
|
100% |
1488
1.80 IPS |
|
|
Pose Estimation (I8)
|
100% |
6335
7.67 IPS |
|
|
Object Detection (F32)
|
100% |
629
47.0 IPS |
|
|
Object Detection (F16)
|
100% |
625
46.7 IPS |
|
|
Object Detection (I8)
|
61% |
1396
104.2 IPS |
|
|
Face Detection (F32)
|
100% |
1452
17.3 IPS |
|
|
Face Detection (F16)
|
100% |
1470
17.5 IPS |
|
|
Face Detection (I8)
|
86% |
2564
30.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
1363
10.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
1403
10.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
2771
21.5 IPS |
|
|
Style Transfer (F32)
|
100% |
2500
3.29 IPS |
|
|
Style Transfer (F16)
|
100% |
2493
3.28 IPS |
|
|
Style Transfer (I8)
|
98% |
5489
7.22 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1028
36.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1087
38.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2509
89.6 IPS |
|
|
Text Classification (F32)
|
100% |
715
1.03 KIPS |
|
|
Text Classification (F16)
|
100% |
685
985.1 IPS |
|
|
Text Classification (I8)
|
92% |
587
844.0 IPS |
|
|
Machine Translation (F32)
|
100% |
1381
25.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1454
26.8 IPS |
|
|
Machine Translation (I8)
|
64% |
635
11.7 IPS |
