samsung SM-G975F
Geekbench ML Score
422
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 07 2024 08:58 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | samsung SM-G975F |
| Model ID | samsung SM-G975F |
| Motherboard | exynos9820 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 83 architecture 8 variant 1 part 3 revision 0 |
| Base Frequency | 1.95 GHz |
| Cluster 1 | 4 Cores @ 1.95 GHz |
| Cluster 2 | 2 Cores @ 2.31 GHz |
| Cluster 3 | 2 Cores @ 2.73 GHz |
| Memory Information | |
|---|---|
| Size | 7.25 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
279
52.3 IPS |
|
|
Image Classification (F16)
|
100% |
384
71.9 IPS |
|
|
Image Classification (I8)
|
97% |
356
66.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
290
4.85 IPS |
|
|
Image Segmentation (F16)
|
100% |
369
6.17 IPS |
|
|
Image Segmentation (I8)
|
98% |
489
8.16 IPS |
|
|
Pose Estimation (F32)
|
100% |
181
0.22 IPS |
|
|
Pose Estimation (F16)
|
100% |
253
0.31 IPS |
|
|
Pose Estimation (I8)
|
100% |
253
0.31 IPS |
|
|
Object Detection (F32)
|
100% |
218
16.3 IPS |
|
|
Object Detection (F16)
|
100% |
281
21.0 IPS |
|
|
Object Detection (I8)
|
62% |
281
21.0 IPS |
|
|
Face Detection (F32)
|
100% |
918
10.9 IPS |
|
|
Face Detection (F16)
|
98% |
1215
14.4 IPS |
|
|
Face Detection (I8)
|
86% |
1238
14.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
466
3.61 IPS |
|
|
Depth Estimation (F16)
|
100% |
641
4.97 IPS |
|
|
Depth Estimation (I8)
|
95% |
534
4.14 IPS |
|
|
Style Transfer (F32)
|
100% |
886
1.17 IPS |
|
|
Style Transfer (F16)
|
100% |
1416
1.86 IPS |
|
|
Style Transfer (I8)
|
98% |
1412
1.86 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
269
9.61 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
363
12.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
360
12.9 IPS |
|
|
Text Classification (F32)
|
100% |
220
316.8 IPS |
|
|
Text Classification (F16)
|
100% |
221
318.0 IPS |
|
|
Text Classification (I8)
|
92% |
359
516.5 IPS |
|
|
Machine Translation (F32)
|
100% |
389
7.17 IPS |
|
|
Machine Translation (F16)
|
100% |
378
6.96 IPS |
|
|
Machine Translation (I8)
|
64% |
416
7.65 IPS |
