samsung SM-S928U1
Geekbench ML Score
1304
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 24 2025 09:59 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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 | 10.83 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
621
116.3 IPS |
|
|
Image Classification (F16)
|
100% |
625
117.0 IPS |
|
|
Image Classification (I8)
|
97% |
1026
192.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
839
14.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
838
14.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
1040
17.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
1521
1.84 IPS |
|
|
Pose Estimation (F16)
|
100% |
1463
1.77 IPS |
|
|
Pose Estimation (I8)
|
100% |
6535
7.91 IPS |
|
|
Object Detection (F32)
|
100% |
622
46.5 IPS |
|
|
Object Detection (F16)
|
100% |
627
46.8 IPS |
|
|
Object Detection (I8)
|
61% |
1407
105.1 IPS |
|
|
Face Detection (F32)
|
100% |
1440
17.1 IPS |
|
|
Face Detection (F16)
|
100% |
1469
17.5 IPS |
|
|
Face Detection (I8)
|
86% |
2570
30.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
1439
11.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
1415
11.0 IPS |
|
|
Depth Estimation (I8)
|
95% |
2798
21.7 IPS |
|
|
Style Transfer (F32)
|
100% |
2608
3.43 IPS |
|
|
Style Transfer (F16)
|
100% |
2517
3.31 IPS |
|
|
Style Transfer (I8)
|
98% |
5316
6.99 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1039
37.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1038
37.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2726
97.3 IPS |
|
|
Text Classification (F32)
|
100% |
731
1.05 KIPS |
|
|
Text Classification (F16)
|
100% |
707
1.02 KIPS |
|
|
Text Classification (I8)
|
92% |
554
796.9 IPS |
|
|
Machine Translation (F32)
|
100% |
1532
28.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1480
27.2 IPS |
|
|
Machine Translation (I8)
|
64% |
601
11.1 IPS |
