samsung SM-X920
Geekbench ML Score
1500
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 27 2024 04:55 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% |
839
157.0 IPS |
|
|
Image Classification (F16)
|
100% |
889
166.3 IPS |
|
|
Image Classification (I8)
|
97% |
1366
255.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
1100
18.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1134
18.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
1255
21.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
1455
1.76 IPS |
|
|
Pose Estimation (F16)
|
100% |
1417
1.72 IPS |
|
|
Pose Estimation (I8)
|
100% |
6440
7.80 IPS |
|
|
Object Detection (F32)
|
100% |
763
57.0 IPS |
|
|
Object Detection (F16)
|
100% |
768
57.3 IPS |
|
|
Object Detection (I8)
|
61% |
1337
99.9 IPS |
|
|
Face Detection (F32)
|
100% |
1934
23.0 IPS |
|
|
Face Detection (F16)
|
100% |
1866
22.2 IPS |
|
|
Face Detection (I8)
|
86% |
2658
31.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
1605
12.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
1645
12.8 IPS |
|
|
Depth Estimation (I8)
|
95% |
2810
21.8 IPS |
|
|
Style Transfer (F32)
|
100% |
2424
3.19 IPS |
|
|
Style Transfer (F16)
|
100% |
2320
3.05 IPS |
|
|
Style Transfer (I8)
|
98% |
5143
6.77 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1052
37.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1056
37.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
3051
108.9 IPS |
|
|
Text Classification (F32)
|
100% |
999
1.44 KIPS |
|
|
Text Classification (F16)
|
100% |
959
1.38 KIPS |
|
|
Text Classification (I8)
|
92% |
765
1.10 KIPS |
|
|
Machine Translation (F32)
|
100% |
1720
31.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1678
30.9 IPS |
|
|
Machine Translation (I8)
|
64% |
784
14.4 IPS |
