samsung SM-S928N
Geekbench ML Score
603
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 09 2024 08:25 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S928N |
| Model ID | samsung SM-S928N |
| 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% |
297
55.5 IPS |
|
|
Image Classification (F16)
|
100% |
288
53.8 IPS |
|
|
Image Classification (I8)
|
97% |
776
145.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
351
5.86 IPS |
|
|
Image Segmentation (F16)
|
100% |
359
6.00 IPS |
|
|
Image Segmentation (I8)
|
98% |
742
12.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
495
0.60 IPS |
|
|
Pose Estimation (F16)
|
100% |
491
0.59 IPS |
|
|
Pose Estimation (I8)
|
100% |
1774
2.15 IPS |
|
|
Object Detection (F32)
|
100% |
274
20.5 IPS |
|
|
Object Detection (F16)
|
100% |
261
19.5 IPS |
|
|
Object Detection (I8)
|
61% |
643
48.0 IPS |
|
|
Face Detection (F32)
|
100% |
633
7.52 IPS |
|
|
Face Detection (F16)
|
100% |
652
7.75 IPS |
|
|
Face Detection (I8)
|
86% |
1512
18.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
567
4.40 IPS |
|
|
Depth Estimation (F16)
|
100% |
564
4.37 IPS |
|
|
Depth Estimation (I8)
|
95% |
1553
12.0 IPS |
|
|
Style Transfer (F32)
|
100% |
929
1.22 IPS |
|
|
Style Transfer (F16)
|
100% |
957
1.26 IPS |
|
|
Style Transfer (I8)
|
98% |
2325
3.06 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
318
11.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
316
11.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1086
38.8 IPS |
|
|
Text Classification (F32)
|
100% |
362
520.6 IPS |
|
|
Text Classification (F16)
|
100% |
367
527.7 IPS |
|
|
Text Classification (I8)
|
92% |
604
868.0 IPS |
|
|
Machine Translation (F32)
|
100% |
697
12.8 IPS |
|
|
Machine Translation (F16)
|
100% |
692
12.7 IPS |
|
|
Machine Translation (I8)
|
64% |
799
14.7 IPS |
