samsung SM-F956U1
Geekbench ML Score
1232
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 11 2024 09:14 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-F956U1 |
| Model ID | samsung SM-F956U1 |
| 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 | 10.86 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
668
125.0 IPS |
|
|
Image Classification (F16)
|
100% |
515
96.3 IPS |
|
|
Image Classification (I8)
|
99% |
329
61.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
894
14.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1373
22.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
1364
22.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
1080
1.31 IPS |
|
|
Pose Estimation (F16)
|
100% |
2660
3.22 IPS |
|
|
Pose Estimation (I8)
|
100% |
2295
2.78 IPS |
|
|
Object Detection (F32)
|
100% |
381
28.4 IPS |
|
|
Object Detection (F16)
|
100% |
369
27.5 IPS |
|
|
Object Detection (I8)
|
62% |
415
31.0 IPS |
|
|
Face Detection (F32)
|
100% |
1865
22.2 IPS |
|
|
Face Detection (F16)
|
97% |
1754
20.9 IPS |
|
|
Face Detection (I8)
|
86% |
2209
26.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
1892
14.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
4010
31.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
3999
31.0 IPS |
|
|
Style Transfer (F32)
|
100% |
7207
9.48 IPS |
|
|
Style Transfer (F16)
|
100% |
11732
15.4 IPS |
|
|
Style Transfer (I8)
|
98% |
10200
13.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
548
19.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1139
40.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1259
45.0 IPS |
|
|
Text Classification (F32)
|
100% |
434
623.5 IPS |
|
|
Text Classification (F16)
|
100% |
432
621.5 IPS |
|
|
Text Classification (I8)
|
92% |
703
1.01 KIPS |
|
|
Machine Translation (F32)
|
100% |
701
12.9 IPS |
|
|
Machine Translation (F16)
|
100% |
667
12.3 IPS |
|
|
Machine Translation (I8)
|
64% |
786
14.5 IPS |
