Samsung Galaxy S23 Ultra
Geekbench ML Score
1013
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 27 2024 09:21 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
452
84.5 IPS |
|
|
Image Classification (F16)
|
100% |
507
94.9 IPS |
|
|
Image Classification (I8)
|
97% |
856
160.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
647
10.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
629
10.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
796
13.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
1190
1.44 IPS |
|
|
Pose Estimation (F16)
|
100% |
1172
1.42 IPS |
|
|
Pose Estimation (I8)
|
100% |
4467
5.41 IPS |
|
|
Object Detection (F32)
|
100% |
493
36.8 IPS |
|
|
Object Detection (F16)
|
100% |
494
36.9 IPS |
|
|
Object Detection (I8)
|
61% |
1164
86.9 IPS |
|
|
Face Detection (F32)
|
100% |
1078
12.8 IPS |
|
|
Face Detection (F16)
|
100% |
1076
12.8 IPS |
|
|
Face Detection (I8)
|
86% |
1883
22.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1134
8.79 IPS |
|
|
Depth Estimation (F16)
|
100% |
1134
8.79 IPS |
|
|
Depth Estimation (I8)
|
95% |
2204
17.1 IPS |
|
|
Style Transfer (F32)
|
100% |
2029
2.67 IPS |
|
|
Style Transfer (F16)
|
100% |
2016
2.65 IPS |
|
|
Style Transfer (I8)
|
98% |
4634
6.10 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
748
26.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
743
26.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2152
76.9 IPS |
|
|
Text Classification (F32)
|
100% |
608
874.0 IPS |
|
|
Text Classification (F16)
|
100% |
576
828.4 IPS |
|
|
Text Classification (I8)
|
92% |
441
633.7 IPS |
|
|
Machine Translation (F32)
|
100% |
1134
20.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1100
20.2 IPS |
|
|
Machine Translation (I8)
|
64% |
488
8.99 IPS |
