samsung SM-S926B
Geekbench ML Score
1766
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 26 2024 09:17 AM |
| Views | 1 |
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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
667
124.8 IPS |
|
|
Image Classification (F16)
|
100% |
811
151.8 IPS |
|
|
Image Classification (I8)
|
99% |
727
136.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
1583
26.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
2217
37.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
1876
31.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
3534
4.28 IPS |
|
|
Pose Estimation (F16)
|
100% |
4453
5.39 IPS |
|
|
Pose Estimation (I8)
|
100% |
4397
5.32 IPS |
|
|
Object Detection (F32)
|
100% |
855
63.8 IPS |
|
|
Object Detection (F16)
|
100% |
710
53.0 IPS |
|
|
Object Detection (I8)
|
58% |
418
31.2 IPS |
|
|
Face Detection (F32)
|
100% |
2476
29.4 IPS |
|
|
Face Detection (F16)
|
97% |
2936
34.9 IPS |
|
|
Face Detection (I8)
|
86% |
2438
29.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
3321
25.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
3870
30.0 IPS |
|
|
Depth Estimation (I8)
|
95% |
3667
28.4 IPS |
|
|
Style Transfer (F32)
|
100% |
9135
12.0 IPS |
|
|
Style Transfer (F16)
|
100% |
13121
17.3 IPS |
|
|
Style Transfer (I8)
|
98% |
13176
17.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1938
69.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2468
88.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2198
78.5 IPS |
|
|
Text Classification (F32)
|
100% |
424
609.4 IPS |
|
|
Text Classification (F16)
|
100% |
428
615.3 IPS |
|
|
Text Classification (I8)
|
92% |
701
1.01 KIPS |
|
|
Machine Translation (F32)
|
100% |
660
12.1 IPS |
|
|
Machine Translation (F16)
|
100% |
643
11.8 IPS |
|
|
Machine Translation (I8)
|
64% |
755
13.9 IPS |
