samsung SM-X716B
Geekbench ML Score
1062
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 19 2024 02:12 AM |
| Views | 2 |
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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
544
101.7 IPS |
|
|
Image Classification (F16)
|
100% |
534
100.0 IPS |
|
|
Image Classification (I8)
|
97% |
859
160.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
693
11.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
652
10.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
810
13.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
1277
1.55 IPS |
|
|
Pose Estimation (F16)
|
100% |
1224
1.48 IPS |
|
|
Pose Estimation (I8)
|
100% |
5208
6.31 IPS |
|
|
Object Detection (F32)
|
100% |
549
41.0 IPS |
|
|
Object Detection (F16)
|
100% |
545
40.7 IPS |
|
|
Object Detection (I8)
|
61% |
1161
86.7 IPS |
|
|
Face Detection (F32)
|
100% |
1165
13.9 IPS |
|
|
Face Detection (F16)
|
100% |
1140
13.6 IPS |
|
|
Face Detection (I8)
|
86% |
1938
23.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
1223
9.49 IPS |
|
|
Depth Estimation (F16)
|
100% |
1187
9.21 IPS |
|
|
Depth Estimation (I8)
|
95% |
2146
16.6 IPS |
|
|
Style Transfer (F32)
|
100% |
2222
2.92 IPS |
|
|
Style Transfer (F16)
|
100% |
2204
2.90 IPS |
|
|
Style Transfer (I8)
|
98% |
4349
5.72 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
834
29.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
788
28.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1953
69.8 IPS |
|
|
Text Classification (F32)
|
100% |
603
866.9 IPS |
|
|
Text Classification (F16)
|
100% |
613
881.3 IPS |
|
|
Text Classification (I8)
|
92% |
446
640.7 IPS |
|
|
Machine Translation (F32)
|
100% |
1242
22.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1218
22.4 IPS |
|
|
Machine Translation (I8)
|
64% |
435
8.00 IPS |
