samsung SM-S926U
Geekbench ML Score
462
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 07 2024 08:58 AM |
| Views | 4 |
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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
268
50.1 IPS |
|
|
Image Classification (F16)
|
100% |
279
52.2 IPS |
|
|
Image Classification (I8)
|
97% |
737
137.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
293
4.90 IPS |
|
|
Image Segmentation (F16)
|
100% |
290
4.84 IPS |
|
|
Image Segmentation (I8)
|
98% |
504
8.41 IPS |
|
|
Pose Estimation (F32)
|
100% |
353
0.43 IPS |
|
|
Pose Estimation (F16)
|
100% |
354
0.43 IPS |
|
|
Pose Estimation (I8)
|
100% |
1290
1.56 IPS |
|
|
Object Detection (F32)
|
100% |
202
15.1 IPS |
|
|
Object Detection (F16)
|
100% |
202
15.1 IPS |
|
|
Object Detection (I8)
|
61% |
541
40.4 IPS |
|
|
Face Detection (F32)
|
100% |
492
5.85 IPS |
|
|
Face Detection (F16)
|
100% |
491
5.84 IPS |
|
|
Face Detection (I8)
|
86% |
1108
13.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
442
3.43 IPS |
|
|
Depth Estimation (F16)
|
100% |
444
3.45 IPS |
|
|
Depth Estimation (I8)
|
95% |
1165
9.04 IPS |
|
|
Style Transfer (F32)
|
100% |
698
0.92 IPS |
|
|
Style Transfer (F16)
|
100% |
700
0.92 IPS |
|
|
Style Transfer (I8)
|
98% |
1636
2.15 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
236
8.42 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
236
8.42 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
777
27.7 IPS |
|
|
Text Classification (F32)
|
100% |
271
389.1 IPS |
|
|
Text Classification (F16)
|
100% |
272
391.2 IPS |
|
|
Text Classification (I8)
|
92% |
447
642.6 IPS |
|
|
Machine Translation (F32)
|
100% |
482
8.86 IPS |
|
|
Machine Translation (F16)
|
100% |
549
10.1 IPS |
|
|
Machine Translation (I8)
|
64% |
577
10.6 IPS |
