samsung SM-S711B
Geekbench ML Score
512
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 24 2024 04:02 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S711B |
| Model ID | samsung SM-S711B |
| Motherboard | s5e9925 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.82 GHz |
| Cluster 1 | 4 Cores @ 1.82 GHz |
| Cluster 2 | 3 Cores @ 2.52 GHz |
| Cluster 3 | 1 Core @ 2.80 GHz |
| Memory Information | |
|---|---|
| Size | 7.12 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
273
51.1 IPS |
|
|
Image Classification (F16)
|
100% |
316
59.2 IPS |
|
|
Image Classification (I8)
|
97% |
432
80.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
343
5.73 IPS |
|
|
Image Segmentation (F16)
|
100% |
261
4.36 IPS |
|
|
Image Segmentation (I8)
|
98% |
291
4.86 IPS |
|
|
Pose Estimation (F32)
|
100% |
811
0.98 IPS |
|
|
Pose Estimation (F16)
|
100% |
785
0.95 IPS |
|
|
Pose Estimation (I8)
|
100% |
2644
3.20 IPS |
|
|
Object Detection (F32)
|
100% |
189
14.1 IPS |
|
|
Object Detection (F16)
|
100% |
248
18.5 IPS |
|
|
Object Detection (I8)
|
61% |
159
11.9 IPS |
|
|
Face Detection (F32)
|
100% |
350
4.17 IPS |
|
|
Face Detection (F16)
|
100% |
377
4.48 IPS |
|
|
Face Detection (I8)
|
86% |
594
7.06 IPS |
|
|
Depth Estimation (F32)
|
100% |
447
3.47 IPS |
|
|
Depth Estimation (F16)
|
100% |
457
3.54 IPS |
|
|
Depth Estimation (I8)
|
95% |
854
6.62 IPS |
|
|
Style Transfer (F32)
|
100% |
1426
1.88 IPS |
|
|
Style Transfer (F16)
|
100% |
1448
1.91 IPS |
|
|
Style Transfer (I8)
|
98% |
2570
3.38 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
558
19.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
623
22.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1261
45.0 IPS |
|
|
Text Classification (F32)
|
100% |
527
757.5 IPS |
|
|
Text Classification (F16)
|
100% |
429
616.1 IPS |
|
|
Text Classification (I8)
|
92% |
257
370.0 IPS |
|
|
Machine Translation (F32)
|
100% |
600
11.0 IPS |
|
|
Machine Translation (F16)
|
100% |
432
7.94 IPS |
|
|
Machine Translation (I8)
|
64% |
341
6.28 IPS |
