Samsung Galaxy S23 Ultra
Geekbench ML Score
915
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 25 2024 11:09 AM |
| Views | 1 |
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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
439
82.1 IPS |
|
|
Image Classification (F16)
|
100% |
427
79.9 IPS |
|
|
Image Classification (I8)
|
97% |
719
134.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
551
9.21 IPS |
|
|
Image Segmentation (F16)
|
100% |
621
10.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
648
10.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
1202
1.46 IPS |
|
|
Pose Estimation (F16)
|
100% |
1141
1.38 IPS |
|
|
Pose Estimation (I8)
|
100% |
4520
5.47 IPS |
|
|
Object Detection (F32)
|
100% |
454
33.9 IPS |
|
|
Object Detection (F16)
|
100% |
463
34.6 IPS |
|
|
Object Detection (I8)
|
61% |
946
70.6 IPS |
|
|
Face Detection (F32)
|
100% |
958
11.4 IPS |
|
|
Face Detection (F16)
|
100% |
993
11.8 IPS |
|
|
Face Detection (I8)
|
86% |
1590
18.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
1053
8.17 IPS |
|
|
Depth Estimation (F16)
|
100% |
1075
8.33 IPS |
|
|
Depth Estimation (I8)
|
95% |
1791
13.9 IPS |
|
|
Style Transfer (F32)
|
100% |
2073
2.73 IPS |
|
|
Style Transfer (F16)
|
100% |
2060
2.71 IPS |
|
|
Style Transfer (I8)
|
98% |
4291
5.64 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
708
25.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
695
24.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1806
64.5 IPS |
|
|
Text Classification (F32)
|
100% |
500
718.4 IPS |
|
|
Text Classification (F16)
|
100% |
510
732.4 IPS |
|
|
Text Classification (I8)
|
92% |
349
502.0 IPS |
|
|
Machine Translation (F32)
|
100% |
1062
19.5 IPS |
|
|
Machine Translation (F16)
|
100% |
1052
19.4 IPS |
|
|
Machine Translation (I8)
|
64% |
392
7.21 IPS |
