samsung SM-X920
Geekbench ML Score
1177
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 27 2024 05:08 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-X920 |
| Model ID | samsung SM-X920 |
| Motherboard | gts10uwifi |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 3 Cores @ 2.85 GHz |
| Cluster 3 | 1 Core @ 3.40 GHz |
| Memory Information | |
|---|---|
| Size | 11.26 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
683
127.8 IPS |
|
|
Image Classification (F16)
|
100% |
704
131.8 IPS |
|
|
Image Classification (I8)
|
97% |
664
124.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
1423
23.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1673
27.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
1617
27.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
772
0.94 IPS |
|
|
Pose Estimation (F16)
|
100% |
1163
1.41 IPS |
|
|
Pose Estimation (I8)
|
100% |
1151
1.39 IPS |
|
|
Object Detection (F32)
|
100% |
425
31.8 IPS |
|
|
Object Detection (F16)
|
100% |
565
42.2 IPS |
|
|
Object Detection (I8)
|
62% |
544
40.6 IPS |
|
|
Face Detection (F32)
|
100% |
2612
31.1 IPS |
|
|
Face Detection (F16)
|
98% |
2641
31.4 IPS |
|
|
Face Detection (I8)
|
86% |
2380
28.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
1597
12.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
2194
17.0 IPS |
|
|
Depth Estimation (I8)
|
95% |
2158
16.7 IPS |
|
|
Style Transfer (F32)
|
100% |
4154
5.46 IPS |
|
|
Style Transfer (F16)
|
100% |
5399
7.10 IPS |
|
|
Style Transfer (I8)
|
98% |
5233
6.88 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
729
26.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
991
35.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1254
44.8 IPS |
|
|
Text Classification (F32)
|
100% |
458
657.6 IPS |
|
|
Text Classification (F16)
|
100% |
462
663.3 IPS |
|
|
Text Classification (I8)
|
92% |
738
1.06 KIPS |
|
|
Machine Translation (F32)
|
100% |
724
13.3 IPS |
|
|
Machine Translation (F16)
|
100% |
708
13.0 IPS |
|
|
Machine Translation (I8)
|
64% |
758
13.9 IPS |
