samsung SM-F956U1
Geekbench ML Score
1047
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 02 2024 12:19 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
589
110.2 IPS |
|
|
Image Classification (F16)
|
100% |
591
110.5 IPS |
|
|
Image Classification (I8)
|
97% |
1031
192.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
753
12.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
651
10.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
782
13.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
1353
1.64 IPS |
|
|
Pose Estimation (F16)
|
100% |
1296
1.57 IPS |
|
|
Pose Estimation (I8)
|
100% |
5658
6.85 IPS |
|
|
Object Detection (F32)
|
100% |
497
37.1 IPS |
|
|
Object Detection (F16)
|
100% |
515
38.4 IPS |
|
|
Object Detection (I8)
|
61% |
1020
76.2 IPS |
|
|
Face Detection (F32)
|
100% |
1211
14.4 IPS |
|
|
Face Detection (F16)
|
100% |
1199
14.3 IPS |
|
|
Face Detection (I8)
|
86% |
2109
25.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
1208
9.36 IPS |
|
|
Depth Estimation (F16)
|
100% |
1183
9.17 IPS |
|
|
Depth Estimation (I8)
|
95% |
2089
16.2 IPS |
|
|
Style Transfer (F32)
|
100% |
2347
3.09 IPS |
|
|
Style Transfer (F16)
|
100% |
2126
2.80 IPS |
|
|
Style Transfer (I8)
|
98% |
3955
5.20 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
681
24.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
677
24.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1668
59.6 IPS |
|
|
Text Classification (F32)
|
100% |
487
700.4 IPS |
|
|
Text Classification (F16)
|
100% |
528
758.1 IPS |
|
|
Text Classification (I8)
|
92% |
397
569.9 IPS |
|
|
Machine Translation (F32)
|
100% |
1173
21.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1354
24.9 IPS |
|
|
Machine Translation (I8)
|
64% |
501
9.22 IPS |
