samsung SM-S926B
Geekbench ML Score
495
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 26 2024 09:21 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S926B |
| Model ID | samsung SM-S926B |
| 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% |
290
54.3 IPS |
|
|
Image Classification (F16)
|
100% |
273
51.1 IPS |
|
|
Image Classification (I8)
|
97% |
732
137.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
857
14.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1278
21.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
737
12.3 IPS |
|
|
Pose Estimation (F32)
|
0
|
||
|
Pose Estimation (F16)
|
0
|
||
|
Pose Estimation (I8)
|
100% |
1950
2.36 IPS |
|
|
Object Detection (F32)
|
100% |
292
21.8 IPS |
|
|
Object Detection (F16)
|
100% |
291
21.7 IPS |
|
|
Object Detection (I8)
|
61% |
797
59.5 IPS |
|
|
Face Detection (F32)
|
100% |
678
8.06 IPS |
|
|
Face Detection (F16)
|
100% |
664
7.90 IPS |
|
|
Face Detection (I8)
|
86% |
1563
18.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
575
4.46 IPS |
|
|
Depth Estimation (F16)
|
100% |
553
4.29 IPS |
|
|
Depth Estimation (I8)
|
95% |
1690
13.1 IPS |
|
|
Style Transfer (F32)
|
100% |
890
1.17 IPS |
|
|
Style Transfer (F16)
|
100% |
896
1.18 IPS |
|
|
Style Transfer (I8)
|
98% |
2314
3.04 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1818
64.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2122
75.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1200
42.9 IPS |
|
|
Text Classification (F32)
|
100% |
419
602.7 IPS |
|
|
Text Classification (F16)
|
100% |
417
599.7 IPS |
|
|
Text Classification (I8)
|
92% |
678
974.6 IPS |
|
|
Machine Translation (F32)
|
100% |
645
11.9 IPS |
|
|
Machine Translation (F16)
|
100% |
614
11.3 IPS |
|
|
Machine Translation (I8)
|
64% |
743
13.7 IPS |
