samsung SM-G998B
Geekbench ML Score
368
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 12 2024 06:58 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-G998B |
| Model ID | samsung SM-G998B |
| Motherboard | exynos9810 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 83 architecture 8 variant 1 part 2 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 4 Cores @ 2.89 GHz |
| Memory Information | |
|---|---|
| Size | 7.54 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
292
54.6 IPS |
|
|
Image Classification (F16)
|
100% |
464
86.8 IPS |
|
|
Image Classification (I8)
|
97% |
441
82.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
272
4.54 IPS |
|
|
Image Segmentation (F16)
|
100% |
416
6.94 IPS |
|
|
Image Segmentation (I8)
|
98% |
416
6.94 IPS |
|
|
Pose Estimation (F32)
|
100% |
125
0.15 IPS |
|
|
Pose Estimation (F16)
|
100% |
179
0.22 IPS |
|
|
Pose Estimation (I8)
|
100% |
179
0.22 IPS |
|
|
Object Detection (F32)
|
100% |
187
13.9 IPS |
|
|
Object Detection (F16)
|
100% |
340
25.4 IPS |
|
|
Object Detection (I8)
|
62% |
348
26.0 IPS |
|
|
Face Detection (F32)
|
100% |
870
10.3 IPS |
|
|
Face Detection (F16)
|
98% |
1334
15.9 IPS |
|
|
Face Detection (I8)
|
86% |
1237
14.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
323
2.50 IPS |
|
|
Depth Estimation (F16)
|
100% |
471
3.65 IPS |
|
|
Depth Estimation (I8)
|
95% |
468
3.63 IPS |
|
|
Style Transfer (F32)
|
100% |
600
0.79 IPS |
|
|
Style Transfer (F16)
|
100% |
1299
1.71 IPS |
|
|
Style Transfer (I8)
|
98% |
1295
1.70 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
271
9.66 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
454
16.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
451
16.1 IPS |
|
|
Text Classification (F32)
|
100% |
196
282.0 IPS |
|
|
Text Classification (F16)
|
100% |
193
277.9 IPS |
|
|
Text Classification (I8)
|
92% |
106
152.1 IPS |
|
|
Machine Translation (F32)
|
100% |
316
5.81 IPS |
|
|
Machine Translation (F16)
|
100% |
319
5.87 IPS |
|
|
Machine Translation (I8)
|
64% |
166
3.05 IPS |
