samsung SM-S936U1
Geekbench ML Score
2138
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 29 2025 03:08 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% |
1326
248.2 IPS |
|
|
Image Classification (F16)
|
100% |
1276
238.7 IPS |
|
|
Image Classification (I8)
|
97% |
1612
301.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
1664
27.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1638
27.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
1791
29.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
2202
2.67 IPS |
|
|
Pose Estimation (F16)
|
100% |
2180
2.64 IPS |
|
|
Pose Estimation (I8)
|
100% |
8755
10.6 IPS |
|
|
Object Detection (F32)
|
100% |
1250
93.3 IPS |
|
|
Object Detection (F16)
|
100% |
1265
94.4 IPS |
|
|
Object Detection (I8)
|
61% |
1976
147.6 IPS |
|
|
Face Detection (F32)
|
100% |
2499
29.7 IPS |
|
|
Face Detection (F16)
|
100% |
2468
29.3 IPS |
|
|
Face Detection (I8)
|
86% |
4415
52.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
2346
18.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
2326
18.0 IPS |
|
|
Depth Estimation (I8)
|
95% |
4586
35.6 IPS |
|
|
Style Transfer (F32)
|
100% |
3592
4.72 IPS |
|
|
Style Transfer (F16)
|
100% |
3553
4.67 IPS |
|
|
Style Transfer (I8)
|
98% |
10174
13.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1411
50.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1424
50.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
4540
162.1 IPS |
|
|
Text Classification (F32)
|
100% |
1190
1.71 KIPS |
|
|
Text Classification (F16)
|
100% |
1173
1.69 KIPS |
|
|
Text Classification (I8)
|
92% |
893
1.28 KIPS |
|
|
Machine Translation (F32)
|
100% |
2140
39.4 IPS |
|
|
Machine Translation (F16)
|
100% |
2104
38.7 IPS |
|
|
Machine Translation (I8)
|
64% |
1014
18.7 IPS |
