samsung SM-X716B
Geekbench ML Score
1009
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | December 02 2025 05:25 PM |
| Views | 9 |
System Information
| System Information | |
|---|---|
| Operating System | Android 16 |
| 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 | 10.92 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
243
45.4 IPS |
|
|
Image Classification (F16)
|
100% |
502
94.0 IPS |
|
|
Image Classification (I8)
|
97% |
862
161.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
661
11.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
652
10.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
775
12.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
1174
1.42 IPS |
|
|
Pose Estimation (F16)
|
100% |
1210
1.47 IPS |
|
|
Pose Estimation (I8)
|
100% |
4983
6.03 IPS |
|
|
Object Detection (F32)
|
100% |
516
38.5 IPS |
|
|
Object Detection (F16)
|
100% |
522
39.0 IPS |
|
|
Object Detection (I8)
|
61% |
1172
87.5 IPS |
|
|
Face Detection (F32)
|
100% |
1095
13.0 IPS |
|
|
Face Detection (F16)
|
100% |
1120
13.3 IPS |
|
|
Face Detection (I8)
|
86% |
1911
22.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
1148
8.90 IPS |
|
|
Depth Estimation (F16)
|
100% |
1147
8.90 IPS |
|
|
Depth Estimation (I8)
|
95% |
2166
16.8 IPS |
|
|
Style Transfer (F32)
|
100% |
2145
2.82 IPS |
|
|
Style Transfer (F16)
|
100% |
2116
2.78 IPS |
|
|
Style Transfer (I8)
|
98% |
4315
5.68 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
777
27.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
746
26.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2162
77.2 IPS |
|
|
Text Classification (F32)
|
100% |
610
877.3 IPS |
|
|
Text Classification (F16)
|
100% |
624
897.3 IPS |
|
|
Text Classification (I8)
|
92% |
455
653.4 IPS |
|
|
Machine Translation (F32)
|
100% |
1181
21.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1138
20.9 IPS |
|
|
Machine Translation (I8)
|
64% |
444
8.17 IPS |
