samsung SM-F956U1
Geekbench ML Score
1140
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 02 2024 12:21 AM |
| 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% |
652
121.9 IPS |
|
|
Image Classification (F16)
|
100% |
511
95.7 IPS |
|
|
Image Classification (I8)
|
99% |
550
103.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
808
13.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
1197
20.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
1152
19.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
891
1.08 IPS |
|
|
Pose Estimation (F16)
|
100% |
1886
2.28 IPS |
|
|
Pose Estimation (I8)
|
100% |
1961
2.37 IPS |
|
|
Object Detection (F32)
|
100% |
594
44.3 IPS |
|
|
Object Detection (F16)
|
100% |
415
31.0 IPS |
|
|
Object Detection (I8)
|
62% |
413
30.8 IPS |
|
|
Face Detection (F32)
|
100% |
1778
21.1 IPS |
|
|
Face Detection (F16)
|
97% |
1743
20.7 IPS |
|
|
Face Detection (I8)
|
86% |
2145
25.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
1440
11.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
3168
24.6 IPS |
|
|
Depth Estimation (I8)
|
95% |
3154
24.5 IPS |
|
|
Style Transfer (F32)
|
100% |
5295
6.96 IPS |
|
|
Style Transfer (F16)
|
100% |
8479
11.2 IPS |
|
|
Style Transfer (I8)
|
98% |
8416
11.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
429
15.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1102
39.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1123
40.1 IPS |
|
|
Text Classification (F32)
|
100% |
419
602.2 IPS |
|
|
Text Classification (F16)
|
100% |
418
600.7 IPS |
|
|
Text Classification (I8)
|
92% |
689
990.6 IPS |
|
|
Machine Translation (F32)
|
100% |
677
12.5 IPS |
|
|
Machine Translation (F16)
|
100% |
640
11.8 IPS |
|
|
Machine Translation (I8)
|
64% |
761
14.0 IPS |
