samsung SM-S936U1
Geekbench ML Score
1564
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 29 2025 03:13 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S936U1 |
| Model ID | samsung SM-S936U1 |
| Motherboard | sun |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.47 GHz |
| Memory Information | |
|---|---|
| Size | 10.86 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
726
135.8 IPS |
|
|
Image Classification (F16)
|
100% |
667
124.8 IPS |
|
|
Image Classification (I8)
|
100% |
700
131.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
936
15.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
1222
20.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
1178
19.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
1653
2.00 IPS |
|
|
Pose Estimation (F16)
|
100% |
2892
3.50 IPS |
|
|
Pose Estimation (I8)
|
100% |
2889
3.50 IPS |
|
|
Object Detection (F32)
|
100% |
374
27.9 IPS |
|
|
Object Detection (F16)
|
100% |
491
36.7 IPS |
|
|
Object Detection (I8)
|
59% |
499
37.3 IPS |
|
|
Face Detection (F32)
|
100% |
2942
35.0 IPS |
|
|
Face Detection (F16)
|
97% |
4265
50.7 IPS |
|
|
Face Detection (I8)
|
86% |
3993
47.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
1677
13.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
4971
38.6 IPS |
|
|
Depth Estimation (I8)
|
94% |
4952
38.4 IPS |
|
|
Style Transfer (F32)
|
100% |
6205
8.16 IPS |
|
|
Style Transfer (F16)
|
100% |
12918
17.0 IPS |
|
|
Style Transfer (I8)
|
98% |
12934
17.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
681
24.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1206
43.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1200
42.9 IPS |
|
|
Text Classification (F32)
|
100% |
656
943.5 IPS |
|
|
Text Classification (F16)
|
100% |
658
946.0 IPS |
|
|
Text Classification (I8)
|
92% |
1049
1.51 KIPS |
|
|
Machine Translation (F32)
|
100% |
1078
19.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1061
19.5 IPS |
|
|
Machine Translation (I8)
|
64% |
1069
19.7 IPS |
