samsung SM-F956U1
Geekbench ML Score
1145
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 11 2024 09:05 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
582
109.0 IPS |
|
|
Image Classification (F16)
|
100% |
592
110.8 IPS |
|
|
Image Classification (I8)
|
97% |
985
184.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
795
13.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
793
13.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
1000
16.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
1319
1.60 IPS |
|
|
Pose Estimation (F16)
|
100% |
1315
1.59 IPS |
|
|
Pose Estimation (I8)
|
100% |
5827
7.06 IPS |
|
|
Object Detection (F32)
|
100% |
577
43.1 IPS |
|
|
Object Detection (F16)
|
100% |
576
43.0 IPS |
|
|
Object Detection (I8)
|
61% |
1229
91.8 IPS |
|
|
Face Detection (F32)
|
100% |
1386
16.5 IPS |
|
|
Face Detection (F16)
|
100% |
1330
15.8 IPS |
|
|
Face Detection (I8)
|
86% |
2218
26.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1317
10.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
1286
9.97 IPS |
|
|
Depth Estimation (I8)
|
95% |
2404
18.6 IPS |
|
|
Style Transfer (F32)
|
100% |
2225
2.93 IPS |
|
|
Style Transfer (F16)
|
100% |
2209
2.91 IPS |
|
|
Style Transfer (I8)
|
98% |
4644
6.11 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
909
32.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
868
31.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2149
76.7 IPS |
|
|
Text Classification (F32)
|
100% |
589
846.3 IPS |
|
|
Text Classification (F16)
|
100% |
553
794.3 IPS |
|
|
Text Classification (I8)
|
92% |
462
664.1 IPS |
|
|
Machine Translation (F32)
|
100% |
1175
21.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1176
21.6 IPS |
|
|
Machine Translation (I8)
|
64% |
496
9.13 IPS |
