samsung SM-S928W
Geekbench ML Score
518
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 15 2024 04:22 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S928W |
| Model ID | samsung SM-S928W |
| 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% |
288
53.9 IPS |
|
|
Image Classification (F16)
|
100% |
275
51.5 IPS |
|
|
Image Classification (I8)
|
97% |
752
140.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
353
5.89 IPS |
|
|
Image Segmentation (F16)
|
100% |
350
5.85 IPS |
|
|
Image Segmentation (I8)
|
98% |
652
10.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
436
0.53 IPS |
|
|
Pose Estimation (F16)
|
100% |
424
0.51 IPS |
|
|
Pose Estimation (I8)
|
100% |
1674
2.03 IPS |
|
|
Object Detection (F32)
|
100% |
246
18.4 IPS |
|
|
Object Detection (F16)
|
100% |
247
18.4 IPS |
|
|
Object Detection (I8)
|
61% |
641
47.8 IPS |
|
|
Face Detection (F32)
|
100% |
609
7.24 IPS |
|
|
Face Detection (F16)
|
100% |
600
7.13 IPS |
|
|
Face Detection (I8)
|
86% |
1272
15.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
485
3.76 IPS |
|
|
Depth Estimation (F16)
|
100% |
475
3.68 IPS |
|
|
Depth Estimation (I8)
|
95% |
1236
9.59 IPS |
|
|
Style Transfer (F32)
|
100% |
770
1.01 IPS |
|
|
Style Transfer (F16)
|
100% |
715
0.94 IPS |
|
|
Style Transfer (I8)
|
98% |
1707
2.24 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
252
9.01 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
250
8.93 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
839
30.0 IPS |
|
|
Text Classification (F32)
|
100% |
277
398.6 IPS |
|
|
Text Classification (F16)
|
100% |
309
443.9 IPS |
|
|
Text Classification (I8)
|
92% |
507
729.1 IPS |
|
|
Machine Translation (F32)
|
100% |
556
10.2 IPS |
|
|
Machine Translation (F16)
|
100% |
553
10.2 IPS |
|
|
Machine Translation (I8)
|
64% |
539
9.92 IPS |
