samsung SM-S928B
Geekbench ML Score
624
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 20 2024 07:29 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S928B |
| Model ID | samsung SM-S928B |
| 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% |
294
55.0 IPS |
|
|
Image Classification (F16)
|
100% |
292
54.7 IPS |
|
|
Image Classification (I8)
|
97% |
776
145.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
371
6.19 IPS |
|
|
Image Segmentation (F16)
|
100% |
365
6.09 IPS |
|
|
Image Segmentation (I8)
|
98% |
761
12.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
498
0.60 IPS |
|
|
Pose Estimation (F16)
|
100% |
490
0.59 IPS |
|
|
Pose Estimation (I8)
|
100% |
1926
2.33 IPS |
|
|
Object Detection (F32)
|
100% |
299
22.3 IPS |
|
|
Object Detection (F16)
|
100% |
299
22.3 IPS |
|
|
Object Detection (I8)
|
61% |
832
62.1 IPS |
|
|
Face Detection (F32)
|
100% |
707
8.41 IPS |
|
|
Face Detection (F16)
|
100% |
700
8.32 IPS |
|
|
Face Detection (I8)
|
86% |
1658
19.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
634
4.91 IPS |
|
|
Depth Estimation (F16)
|
100% |
637
4.94 IPS |
|
|
Depth Estimation (I8)
|
95% |
1787
13.9 IPS |
|
|
Style Transfer (F32)
|
100% |
1000
1.32 IPS |
|
|
Style Transfer (F16)
|
100% |
986
1.30 IPS |
|
|
Style Transfer (I8)
|
98% |
2358
3.10 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
322
11.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
320
11.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1076
38.4 IPS |
|
|
Text Classification (F32)
|
100% |
355
510.7 IPS |
|
|
Text Classification (F16)
|
100% |
353
506.6 IPS |
|
|
Text Classification (I8)
|
92% |
579
831.7 IPS |
|
|
Machine Translation (F32)
|
100% |
652
12.0 IPS |
|
|
Machine Translation (F16)
|
100% |
639
11.8 IPS |
|
|
Machine Translation (I8)
|
64% |
650
12.0 IPS |
