Samsung Galaxy S23 Ultra
Geekbench ML Score
1048
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | June 15 2025 06:21 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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 | 10.79 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
526
98.4 IPS |
|
|
Image Classification (F16)
|
100% |
510
95.5 IPS |
|
|
Image Classification (I8)
|
97% |
837
156.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
682
11.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
644
10.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
796
13.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
1228
1.49 IPS |
|
|
Pose Estimation (F16)
|
100% |
1225
1.48 IPS |
|
|
Pose Estimation (I8)
|
100% |
5039
6.10 IPS |
|
|
Object Detection (F32)
|
100% |
550
41.1 IPS |
|
|
Object Detection (F16)
|
100% |
535
39.9 IPS |
|
|
Object Detection (I8)
|
61% |
1180
88.1 IPS |
|
|
Face Detection (F32)
|
100% |
1151
13.7 IPS |
|
|
Face Detection (F16)
|
100% |
1117
13.3 IPS |
|
|
Face Detection (I8)
|
86% |
1994
23.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
1170
9.08 IPS |
|
|
Depth Estimation (F16)
|
100% |
1187
9.21 IPS |
|
|
Depth Estimation (I8)
|
95% |
2164
16.8 IPS |
|
|
Style Transfer (F32)
|
100% |
2125
2.79 IPS |
|
|
Style Transfer (F16)
|
100% |
2097
2.76 IPS |
|
|
Style Transfer (I8)
|
98% |
4356
5.73 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
793
28.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
779
27.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2178
77.8 IPS |
|
|
Text Classification (F32)
|
100% |
608
873.7 IPS |
|
|
Text Classification (F16)
|
100% |
606
871.4 IPS |
|
|
Text Classification (I8)
|
92% |
455
653.8 IPS |
|
|
Machine Translation (F32)
|
100% |
1198
22.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1145
21.1 IPS |
|
|
Machine Translation (I8)
|
64% |
437
8.03 IPS |
