samsung SM-S711B
Geekbench ML Score
313
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 19 2024 06:45 AM |
| Views | 2 |
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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
174
32.6 IPS |
|
|
Image Classification (F16)
|
100% |
175
32.8 IPS |
|
|
Image Classification (I8)
|
97% |
414
77.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
164
2.74 IPS |
|
|
Image Segmentation (F16)
|
100% |
195
3.26 IPS |
|
|
Image Segmentation (I8)
|
98% |
468
7.82 IPS |
|
|
Pose Estimation (F32)
|
100% |
224
0.27 IPS |
|
|
Pose Estimation (F16)
|
100% |
220
0.27 IPS |
|
|
Pose Estimation (I8)
|
100% |
906
1.10 IPS |
|
|
Object Detection (F32)
|
100% |
133
9.96 IPS |
|
|
Object Detection (F16)
|
100% |
134
9.97 IPS |
|
|
Object Detection (I8)
|
61% |
397
29.6 IPS |
|
|
Face Detection (F32)
|
100% |
358
4.25 IPS |
|
|
Face Detection (F16)
|
100% |
360
4.28 IPS |
|
|
Face Detection (I8)
|
86% |
845
10.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
297
2.30 IPS |
|
|
Depth Estimation (F16)
|
100% |
295
2.29 IPS |
|
|
Depth Estimation (I8)
|
95% |
866
6.71 IPS |
|
|
Style Transfer (F32)
|
100% |
509
0.67 IPS |
|
|
Style Transfer (F16)
|
100% |
509
0.67 IPS |
|
|
Style Transfer (I8)
|
98% |
1298
1.71 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
148
5.30 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
149
5.30 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
553
19.7 IPS |
|
|
Text Classification (F32)
|
100% |
168
241.7 IPS |
|
|
Text Classification (F16)
|
100% |
169
242.6 IPS |
|
|
Text Classification (I8)
|
92% |
314
451.3 IPS |
|
|
Machine Translation (F32)
|
100% |
330
6.06 IPS |
|
|
Machine Translation (F16)
|
100% |
316
5.82 IPS |
|
|
Machine Translation (I8)
|
64% |
394
7.25 IPS |
