samsung SM-S928N
Geekbench ML Score
1299
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| User | Cho_Seung_Woo |
| Upload Date | February 23 2024 02:57 AM |
| Views | 3 |
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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
743
139.0 IPS |
|
|
Image Classification (F16)
|
100% |
793
148.3 IPS |
|
|
Image Classification (I8)
|
99% |
746
139.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
850
14.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
1226
20.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
1020
17.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
1078
1.31 IPS |
|
|
Pose Estimation (F16)
|
100% |
2657
3.22 IPS |
|
|
Pose Estimation (I8)
|
100% |
2672
3.24 IPS |
|
|
Object Detection (F32)
|
100% |
277
20.7 IPS |
|
|
Object Detection (F16)
|
100% |
261
19.5 IPS |
|
|
Object Detection (I8)
|
62% |
374
27.9 IPS |
|
|
Face Detection (F32)
|
100% |
2998
35.6 IPS |
|
|
Face Detection (F16)
|
97% |
2985
35.5 IPS |
|
|
Face Detection (I8)
|
86% |
2472
29.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1899
14.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
3942
30.6 IPS |
|
|
Depth Estimation (I8)
|
95% |
3998
31.0 IPS |
|
|
Style Transfer (F32)
|
100% |
7268
9.56 IPS |
|
|
Style Transfer (F16)
|
100% |
11743
15.4 IPS |
|
|
Style Transfer (I8)
|
98% |
11679
15.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
563
20.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1142
40.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1151
41.1 IPS |
|
|
Text Classification (F32)
|
100% |
437
627.5 IPS |
|
|
Text Classification (F16)
|
100% |
438
629.1 IPS |
|
|
Text Classification (I8)
|
92% |
712
1.02 KIPS |
|
|
Machine Translation (F32)
|
100% |
709
13.0 IPS |
|
|
Machine Translation (F16)
|
100% |
702
12.9 IPS |
|
|
Machine Translation (I8)
|
64% |
818
15.1 IPS |
