samsung SM-X716B
Geekbench ML Score
1070
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 16 2025 08:36 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-X716B |
| Model ID | samsung SM-X716B |
| Motherboard | kalama |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3406 revision 0 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 3 Cores @ 2.02 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Cluster 3 | 1 Core @ 3.36 GHz |
| Memory Information | |
|---|---|
| Size | 10.91 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
656
122.8 IPS |
|
|
Image Classification (F16)
|
100% |
921
172.4 IPS |
|
|
Image Classification (I8)
|
99% |
682
127.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
842
14.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
1150
19.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
946
15.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
970
1.17 IPS |
|
|
Pose Estimation (F16)
|
100% |
1392
1.69 IPS |
|
|
Pose Estimation (I8)
|
100% |
1389
1.68 IPS |
|
|
Object Detection (F32)
|
100% |
269
20.1 IPS |
|
|
Object Detection (F16)
|
100% |
394
29.4 IPS |
|
|
Object Detection (I8)
|
62% |
406
30.3 IPS |
|
|
Face Detection (F32)
|
100% |
2242
26.7 IPS |
|
|
Face Detection (F16)
|
97% |
3030
36.0 IPS |
|
|
Face Detection (I8)
|
86% |
2883
34.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
1500
11.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
2946
22.8 IPS |
|
|
Depth Estimation (I8)
|
95% |
2856
22.1 IPS |
|
|
Style Transfer (F32)
|
100% |
3788
4.98 IPS |
|
|
Style Transfer (F16)
|
100% |
8562
11.3 IPS |
|
|
Style Transfer (I8)
|
98% |
8532
11.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
456
16.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
392
14.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
392
14.0 IPS |
|
|
Text Classification (F32)
|
100% |
462
664.4 IPS |
|
|
Text Classification (F16)
|
100% |
460
661.0 IPS |
|
|
Text Classification (I8)
|
92% |
684
982.3 IPS |
|
|
Machine Translation (F32)
|
100% |
710
13.1 IPS |
|
|
Machine Translation (F16)
|
100% |
691
12.7 IPS |
|
|
Machine Translation (I8)
|
64% |
747
13.7 IPS |
