samsung SM-S926U
Geekbench ML Score
1263
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 07 2024 02:14 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S926U |
| Model ID | samsung SM-S926U |
| Motherboard | pineapple |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.40 GHz |
| Memory Information | |
|---|---|
| Size | 10.81 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
587
109.8 IPS |
|
|
Image Classification (F16)
|
100% |
590
110.4 IPS |
|
|
Image Classification (I8)
|
97% |
1051
196.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
794
13.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
780
13.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
959
16.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
1331
1.61 IPS |
|
|
Pose Estimation (F16)
|
100% |
1264
1.53 IPS |
|
|
Pose Estimation (I8)
|
100% |
5898
7.14 IPS |
|
|
Object Detection (F32)
|
100% |
619
46.2 IPS |
|
|
Object Detection (F16)
|
100% |
629
46.9 IPS |
|
|
Object Detection (I8)
|
61% |
1368
102.1 IPS |
|
|
Face Detection (F32)
|
100% |
1406
16.7 IPS |
|
|
Face Detection (F16)
|
100% |
1406
16.7 IPS |
|
|
Face Detection (I8)
|
86% |
2516
29.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
1413
11.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
1430
11.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
2844
22.1 IPS |
|
|
Style Transfer (F32)
|
100% |
2350
3.09 IPS |
|
|
Style Transfer (F16)
|
100% |
2256
2.97 IPS |
|
|
Style Transfer (I8)
|
98% |
5262
6.92 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
984
35.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1071
38.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2690
96.1 IPS |
|
|
Text Classification (F32)
|
100% |
780
1.12 KIPS |
|
|
Text Classification (F16)
|
100% |
767
1.10 KIPS |
|
|
Text Classification (I8)
|
92% |
561
805.9 IPS |
|
|
Machine Translation (F32)
|
100% |
1468
27.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1431
26.3 IPS |
|
|
Machine Translation (I8)
|
64% |
619
11.4 IPS |
