samsung SM-S928B
Geekbench ML Score
1140
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 26 2025 03:00 PM |
| Views | 6 |
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 | 10.83 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
480
89.8 IPS |
|
|
Image Classification (F16)
|
100% |
491
91.9 IPS |
|
|
Image Classification (I8)
|
97% |
936
175.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
682
11.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
669
11.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
816
13.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
1467
1.78 IPS |
|
|
Pose Estimation (F16)
|
100% |
1439
1.74 IPS |
|
|
Pose Estimation (I8)
|
100% |
5621
6.81 IPS |
|
|
Object Detection (F32)
|
100% |
521
38.9 IPS |
|
|
Object Detection (F16)
|
100% |
526
39.2 IPS |
|
|
Object Detection (I8)
|
61% |
1023
76.4 IPS |
|
|
Face Detection (F32)
|
100% |
1191
14.2 IPS |
|
|
Face Detection (F16)
|
100% |
1202
14.3 IPS |
|
|
Face Detection (I8)
|
86% |
2291
27.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
1308
10.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
1275
9.89 IPS |
|
|
Depth Estimation (I8)
|
95% |
2299
17.8 IPS |
|
|
Style Transfer (F32)
|
100% |
2494
3.28 IPS |
|
|
Style Transfer (F16)
|
100% |
2486
3.27 IPS |
|
|
Style Transfer (I8)
|
98% |
5647
7.43 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
984
35.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1006
35.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2369
84.6 IPS |
|
|
Text Classification (F32)
|
100% |
611
878.8 IPS |
|
|
Text Classification (F16)
|
100% |
602
865.1 IPS |
|
|
Text Classification (I8)
|
92% |
463
665.5 IPS |
|
|
Machine Translation (F32)
|
100% |
1369
25.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1379
25.4 IPS |
|
|
Machine Translation (I8)
|
64% |
571
10.5 IPS |
