samsung SM-X516B
Geekbench ML Score
330
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 19 2024 06:39 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-X516B |
| Model ID | samsung SM-X516B |
| Motherboard | s5e8835 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 7.26 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
125
23.4 IPS |
|
|
Image Classification (F16)
|
100% |
125
23.4 IPS |
|
|
Image Classification (I8)
|
97% |
335
62.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
296
4.95 IPS |
|
|
Image Segmentation (F16)
|
100% |
434
7.24 IPS |
|
|
Image Segmentation (I8)
|
98% |
367
6.13 IPS |
|
|
Pose Estimation (F32)
|
100% |
85
0.10 IPS |
|
|
Pose Estimation (F16)
|
100% |
2377
2.88 IPS |
|
|
Pose Estimation (I8)
|
100% |
850
1.03 IPS |
|
|
Object Detection (F32)
|
100% |
131
9.80 IPS |
|
|
Object Detection (F16)
|
100% |
131
9.81 IPS |
|
|
Object Detection (I8)
|
61% |
373
27.9 IPS |
|
|
Face Detection (F32)
|
100% |
325
3.87 IPS |
|
|
Face Detection (F16)
|
100% |
325
3.87 IPS |
|
|
Face Detection (I8)
|
86% |
736
8.75 IPS |
|
|
Depth Estimation (F32)
|
100% |
274
2.13 IPS |
|
|
Depth Estimation (F16)
|
100% |
275
2.13 IPS |
|
|
Depth Estimation (I8)
|
95% |
795
6.17 IPS |
|
|
Style Transfer (F32)
|
100% |
467
0.61 IPS |
|
|
Style Transfer (F16)
|
100% |
468
0.62 IPS |
|
|
Style Transfer (I8)
|
98% |
1307
1.72 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
76
2.70 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
887
31.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
484
17.3 IPS |
|
|
Text Classification (F32)
|
100% |
167
240.6 IPS |
|
|
Text Classification (F16)
|
100% |
166
238.1 IPS |
|
|
Text Classification (I8)
|
92% |
323
464.3 IPS |
|
|
Machine Translation (F32)
|
100% |
304
5.60 IPS |
|
|
Machine Translation (F16)
|
100% |
304
5.59 IPS |
|
|
Machine Translation (I8)
|
64% |
394
7.25 IPS |
