samsung SM-S926N
Geekbench ML Score
1568
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 26 2024 02:11 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S926N |
| Model ID | samsung SM-S926N |
| Motherboard | s5e9945 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 10 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 1.96 GHz |
| Cluster 1 | 4 Cores @ 1.96 GHz |
| Cluster 2 | 3 Cores @ 2.59 GHz |
| Cluster 3 | 2 Cores @ 2.90 GHz |
| Cluster 4 | 1 Core @ 3.21 GHz |
| Memory Information | |
|---|---|
| Size | 10.95 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
647
121.1 IPS |
|
|
Image Classification (F16)
|
100% |
765
143.1 IPS |
|
|
Image Classification (I8)
|
99% |
684
127.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
1450
24.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
2046
34.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
1972
32.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
2827
3.42 IPS |
|
|
Pose Estimation (F16)
|
100% |
3428
4.15 IPS |
|
|
Pose Estimation (I8)
|
100% |
3564
4.32 IPS |
|
|
Object Detection (F32)
|
100% |
601
44.9 IPS |
|
|
Object Detection (F16)
|
100% |
605
45.1 IPS |
|
|
Object Detection (I8)
|
58% |
364
27.2 IPS |
|
|
Face Detection (F32)
|
100% |
2190
26.0 IPS |
|
|
Face Detection (F16)
|
97% |
2664
31.7 IPS |
|
|
Face Detection (I8)
|
86% |
2364
28.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
3065
23.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
3656
28.4 IPS |
|
|
Depth Estimation (I8)
|
95% |
3588
27.8 IPS |
|
|
Style Transfer (F32)
|
100% |
7361
9.68 IPS |
|
|
Style Transfer (F16)
|
100% |
10464
13.8 IPS |
|
|
Style Transfer (I8)
|
98% |
9843
12.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1602
57.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2238
79.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2090
74.6 IPS |
|
|
Text Classification (F32)
|
100% |
396
569.0 IPS |
|
|
Text Classification (F16)
|
100% |
399
574.1 IPS |
|
|
Text Classification (I8)
|
92% |
652
936.7 IPS |
|
|
Machine Translation (F32)
|
100% |
607
11.2 IPS |
|
|
Machine Translation (F16)
|
100% |
596
11.0 IPS |
|
|
Machine Translation (I8)
|
64% |
695
12.8 IPS |
