samsung SM-X920
Geekbench ML Score
1481
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 27 2024 04:58 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
891
166.8 IPS |
|
|
Image Classification (F16)
|
100% |
919
171.9 IPS |
|
|
Image Classification (I8)
|
97% |
1358
254.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
1088
18.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
1141
19.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
1243
20.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
1473
1.78 IPS |
|
|
Pose Estimation (F16)
|
100% |
1378
1.67 IPS |
|
|
Pose Estimation (I8)
|
100% |
6402
7.75 IPS |
|
|
Object Detection (F32)
|
100% |
746
55.7 IPS |
|
|
Object Detection (F16)
|
100% |
755
56.4 IPS |
|
|
Object Detection (I8)
|
61% |
1344
100.3 IPS |
|
|
Face Detection (F32)
|
100% |
1944
23.1 IPS |
|
|
Face Detection (F16)
|
100% |
1840
21.9 IPS |
|
|
Face Detection (I8)
|
86% |
2490
29.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
1638
12.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
1564
12.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
2712
21.0 IPS |
|
|
Style Transfer (F32)
|
100% |
2388
3.14 IPS |
|
|
Style Transfer (F16)
|
100% |
2334
3.07 IPS |
|
|
Style Transfer (I8)
|
98% |
5220
6.87 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1030
36.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1043
37.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2910
103.9 IPS |
|
|
Text Classification (F32)
|
100% |
990
1.42 KIPS |
|
|
Text Classification (F16)
|
100% |
974
1.40 KIPS |
|
|
Text Classification (I8)
|
92% |
776
1.12 KIPS |
|
|
Machine Translation (F32)
|
100% |
1728
31.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1685
31.0 IPS |
|
|
Machine Translation (I8)
|
64% |
635
11.7 IPS |
