Samsung Galaxy S23 Ultra
Geekbench ML Score
937
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 01 2024 07:36 AM |
| 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% |
542
101.4 IPS |
|
|
Image Classification (F16)
|
100% |
796
148.9 IPS |
|
|
Image Classification (I8)
|
99% |
737
137.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
1003
16.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1248
20.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
1427
23.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
876
1.06 IPS |
|
|
Pose Estimation (F16)
|
100% |
1128
1.37 IPS |
|
|
Pose Estimation (I8)
|
100% |
1098
1.33 IPS |
|
|
Object Detection (F32)
|
100% |
312
23.3 IPS |
|
|
Object Detection (F16)
|
100% |
361
27.0 IPS |
|
|
Object Detection (I8)
|
62% |
366
27.3 IPS |
|
|
Face Detection (F32)
|
100% |
1970
23.4 IPS |
|
|
Face Detection (F16)
|
97% |
1767
21.0 IPS |
|
|
Face Detection (I8)
|
86% |
1958
23.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
1408
10.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
2687
20.8 IPS |
|
|
Depth Estimation (I8)
|
95% |
2631
20.4 IPS |
|
|
Style Transfer (F32)
|
100% |
3326
4.38 IPS |
|
|
Style Transfer (F16)
|
100% |
6936
9.12 IPS |
|
|
Style Transfer (I8)
|
98% |
6812
8.96 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
381
13.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
324
11.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
356
12.7 IPS |
|
|
Text Classification (F32)
|
100% |
343
493.7 IPS |
|
|
Text Classification (F16)
|
100% |
343
492.5 IPS |
|
|
Text Classification (I8)
|
92% |
503
722.4 IPS |
|
|
Machine Translation (F32)
|
100% |
586
10.8 IPS |
|
|
Machine Translation (F16)
|
100% |
590
10.9 IPS |
|
|
Machine Translation (I8)
|
64% |
591
10.9 IPS |
