samsung SM-S936U1
Geekbench ML Score
2072
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 29 2025 03:09 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1240
232.1 IPS |
|
|
Image Classification (F16)
|
100% |
1228
229.8 IPS |
|
|
Image Classification (I8)
|
97% |
1590
297.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
1633
27.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1601
26.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
1673
27.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
2185
2.65 IPS |
|
|
Pose Estimation (F16)
|
100% |
2169
2.63 IPS |
|
|
Pose Estimation (I8)
|
100% |
8543
10.3 IPS |
|
|
Object Detection (F32)
|
100% |
1140
85.1 IPS |
|
|
Object Detection (F16)
|
100% |
1145
85.4 IPS |
|
|
Object Detection (I8)
|
61% |
1448
108.1 IPS |
|
|
Face Detection (F32)
|
100% |
2499
29.7 IPS |
|
|
Face Detection (F16)
|
100% |
2449
29.1 IPS |
|
|
Face Detection (I8)
|
86% |
4417
52.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
2342
18.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
2323
18.0 IPS |
|
|
Depth Estimation (I8)
|
95% |
4445
34.5 IPS |
|
|
Style Transfer (F32)
|
100% |
3587
4.72 IPS |
|
|
Style Transfer (F16)
|
100% |
3533
4.65 IPS |
|
|
Style Transfer (I8)
|
98% |
10052
13.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1414
50.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1416
50.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
4625
165.2 IPS |
|
|
Text Classification (F32)
|
100% |
1175
1.69 KIPS |
|
|
Text Classification (F16)
|
100% |
1171
1.68 KIPS |
|
|
Text Classification (I8)
|
92% |
850
1.22 KIPS |
|
|
Machine Translation (F32)
|
100% |
2119
39.0 IPS |
|
|
Machine Translation (F16)
|
100% |
2043
37.6 IPS |
|
|
Machine Translation (I8)
|
64% |
987
18.2 IPS |
