Samsung Galaxy S23 Ultra
Geekbench ML Score
1054
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 28 2024 04:16 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 Ultra |
| Model ID | samsung SM-S918B |
| Motherboard | kalama |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3406 revision 0 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 3 Cores @ 2.02 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Cluster 3 | 1 Core @ 3.36 GHz |
| Memory Information | |
|---|---|
| Size | 10.77 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
659
123.3 IPS |
|
|
Image Classification (F16)
|
100% |
842
157.6 IPS |
|
|
Image Classification (I8)
|
99% |
686
128.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
1032
17.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
1210
20.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
1314
21.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
966
1.17 IPS |
|
|
Pose Estimation (F16)
|
100% |
1385
1.68 IPS |
|
|
Pose Estimation (I8)
|
100% |
1388
1.68 IPS |
|
|
Object Detection (F32)
|
100% |
354
26.4 IPS |
|
|
Object Detection (F16)
|
100% |
427
31.9 IPS |
|
|
Object Detection (I8)
|
62% |
407
30.4 IPS |
|
|
Face Detection (F32)
|
100% |
2211
26.3 IPS |
|
|
Face Detection (F16)
|
97% |
2305
27.4 IPS |
|
|
Face Detection (I8)
|
86% |
1679
20.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
1494
11.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
2891
22.4 IPS |
|
|
Depth Estimation (I8)
|
95% |
2841
22.0 IPS |
|
|
Style Transfer (F32)
|
100% |
3765
4.95 IPS |
|
|
Style Transfer (F16)
|
100% |
8524
11.2 IPS |
|
|
Style Transfer (I8)
|
98% |
8492
11.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
474
16.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
388
13.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
387
13.8 IPS |
|
|
Text Classification (F32)
|
100% |
414
595.0 IPS |
|
|
Text Classification (F16)
|
100% |
424
609.9 IPS |
|
|
Text Classification (I8)
|
92% |
670
962.4 IPS |
|
|
Machine Translation (F32)
|
100% |
654
12.0 IPS |
|
|
Machine Translation (F16)
|
100% |
641
11.8 IPS |
|
|
Machine Translation (I8)
|
64% |
687
12.6 IPS |
