samsung SM-S926B
Geekbench ML Score
1144
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 26 2024 09:13 AM |
| Views | 3 |
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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
567
106.1 IPS |
|
|
Image Classification (F16)
|
100% |
528
98.7 IPS |
|
|
Image Classification (I8)
|
97% |
890
166.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
810
13.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
788
13.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
832
13.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
1364
1.65 IPS |
|
|
Pose Estimation (F16)
|
100% |
1320
1.60 IPS |
|
|
Pose Estimation (I8)
|
100% |
5928
7.18 IPS |
|
|
Object Detection (F32)
|
100% |
566
42.2 IPS |
|
|
Object Detection (F16)
|
100% |
566
42.2 IPS |
|
|
Object Detection (I8)
|
61% |
1297
96.8 IPS |
|
|
Face Detection (F32)
|
100% |
1295
15.4 IPS |
|
|
Face Detection (F16)
|
100% |
1309
15.6 IPS |
|
|
Face Detection (I8)
|
86% |
2309
27.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
1283
9.95 IPS |
|
|
Depth Estimation (F16)
|
100% |
1324
10.3 IPS |
|
|
Depth Estimation (I8)
|
95% |
2405
18.6 IPS |
|
|
Style Transfer (F32)
|
100% |
2044
2.69 IPS |
|
|
Style Transfer (F16)
|
100% |
2194
2.89 IPS |
|
|
Style Transfer (I8)
|
98% |
5181
6.82 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
924
33.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
867
31.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2521
90.0 IPS |
|
|
Text Classification (F32)
|
100% |
655
941.1 IPS |
|
|
Text Classification (F16)
|
100% |
636
913.9 IPS |
|
|
Text Classification (I8)
|
92% |
495
711.4 IPS |
|
|
Machine Translation (F32)
|
100% |
1214
22.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1134
20.9 IPS |
|
|
Machine Translation (I8)
|
64% |
427
7.85 IPS |
