samsung SM-S928U
Geekbench ML Score
755
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 28 2024 12:28 AM |
| 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% |
414
77.4 IPS |
|
|
Image Classification (F16)
|
100% |
414
77.4 IPS |
|
|
Image Classification (I8)
|
97% |
639
119.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
534
8.92 IPS |
|
|
Image Segmentation (F16)
|
100% |
492
8.21 IPS |
|
|
Image Segmentation (I8)
|
98% |
597
9.97 IPS |
|
|
Pose Estimation (F32)
|
100% |
1236
1.50 IPS |
|
|
Pose Estimation (F16)
|
100% |
1253
1.52 IPS |
|
|
Pose Estimation (I8)
|
100% |
4122
4.99 IPS |
|
|
Object Detection (F32)
|
100% |
360
26.9 IPS |
|
|
Object Detection (F16)
|
100% |
383
28.6 IPS |
|
|
Object Detection (I8)
|
61% |
774
57.8 IPS |
|
|
Face Detection (F32)
|
100% |
911
10.8 IPS |
|
|
Face Detection (F16)
|
100% |
914
10.9 IPS |
|
|
Face Detection (I8)
|
86% |
1598
19.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
934
7.25 IPS |
|
|
Depth Estimation (F16)
|
100% |
895
6.94 IPS |
|
|
Depth Estimation (I8)
|
95% |
1527
11.8 IPS |
|
|
Style Transfer (F32)
|
100% |
1938
2.55 IPS |
|
|
Style Transfer (F16)
|
100% |
1741
2.29 IPS |
|
|
Style Transfer (I8)
|
98% |
3138
4.13 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
517
18.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
486
17.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1283
45.8 IPS |
|
|
Text Classification (F32)
|
100% |
314
451.0 IPS |
|
|
Text Classification (F16)
|
100% |
327
469.5 IPS |
|
|
Text Classification (I8)
|
92% |
232
333.9 IPS |
|
|
Machine Translation (F32)
|
100% |
639
11.8 IPS |
|
|
Machine Translation (F16)
|
100% |
680
12.5 IPS |
|
|
Machine Translation (I8)
|
64% |
319
5.88 IPS |
