samsung SM-S926N
Geekbench ML Score
362
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 26 2024 02:18 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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
263
49.2 IPS |
|
|
Image Classification (F16)
|
100% |
249
46.5 IPS |
|
|
Image Classification (I8)
|
97% |
631
118.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
826
13.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1134
18.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
565
9.44 IPS |
|
|
Pose Estimation (F32)
|
0
|
||
|
Pose Estimation (F16)
|
0
|
||
|
Pose Estimation (I8)
|
100% |
1523
1.84 IPS |
|
|
Object Detection (F32)
|
100% |
232
17.3 IPS |
|
|
Object Detection (F16)
|
100% |
232
17.3 IPS |
|
|
Object Detection (I8)
|
61% |
371
27.7 IPS |
|
|
Face Detection (F32)
|
100% |
556
6.61 IPS |
|
|
Face Detection (F16)
|
100% |
516
6.14 IPS |
|
|
Face Detection (I8)
|
86% |
1113
13.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
437
3.39 IPS |
|
|
Depth Estimation (F16)
|
100% |
418
3.24 IPS |
|
|
Depth Estimation (I8)
|
95% |
1027
7.97 IPS |
|
|
Style Transfer (F32)
|
100% |
642
0.84 IPS |
|
|
Style Transfer (F16)
|
100% |
589
0.77 IPS |
|
|
Style Transfer (I8)
|
98% |
1372
1.80 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1600
57.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2106
75.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
631
22.5 IPS |
|
|
Text Classification (F32)
|
100% |
228
328.1 IPS |
|
|
Text Classification (F16)
|
100% |
127
182.6 IPS |
|
|
Text Classification (I8)
|
92% |
380
545.5 IPS |
|
|
Machine Translation (F32)
|
100% |
475
8.74 IPS |
|
|
Machine Translation (F16)
|
100% |
495
9.12 IPS |
|
|
Machine Translation (I8)
|
64% |
551
10.1 IPS |
