Samsung Galaxy S23 Ultra
Geekbench ML Score
1005
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 20 2024 05:30 AM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 Ultra |
| Model ID | samsung SM-S9180 |
| 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% |
641
119.9 IPS |
|
|
Image Classification (F16)
|
100% |
966
180.8 IPS |
|
|
Image Classification (I8)
|
99% |
831
155.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
941
15.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1188
19.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
1206
20.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
869
1.05 IPS |
|
|
Pose Estimation (F16)
|
100% |
1161
1.41 IPS |
|
|
Pose Estimation (I8)
|
100% |
1149
1.39 IPS |
|
|
Object Detection (F32)
|
100% |
353
26.4 IPS |
|
|
Object Detection (F16)
|
100% |
453
33.8 IPS |
|
|
Object Detection (I8)
|
62% |
403
30.1 IPS |
|
|
Face Detection (F32)
|
100% |
1912
22.7 IPS |
|
|
Face Detection (F16)
|
97% |
2357
28.0 IPS |
|
|
Face Detection (I8)
|
86% |
2679
31.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
1274
9.88 IPS |
|
|
Depth Estimation (F16)
|
100% |
2694
20.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
2693
20.9 IPS |
|
|
Style Transfer (F32)
|
100% |
3055
4.02 IPS |
|
|
Style Transfer (F16)
|
100% |
7905
10.4 IPS |
|
|
Style Transfer (I8)
|
98% |
7939
10.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
376
13.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
269
9.59 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
284
10.2 IPS |
|
|
Text Classification (F32)
|
100% |
427
613.8 IPS |
|
|
Text Classification (F16)
|
100% |
440
632.3 IPS |
|
|
Text Classification (I8)
|
92% |
684
982.9 IPS |
|
|
Machine Translation (F32)
|
100% |
658
12.1 IPS |
|
|
Machine Translation (F16)
|
100% |
634
11.7 IPS |
|
|
Machine Translation (I8)
|
64% |
686
12.6 IPS |
