Samsung Galaxy S23 Ultra
Geekbench ML Score
931
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 20 2024 04:53 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
654
122.4 IPS |
|
|
Image Classification (F16)
|
100% |
722
135.2 IPS |
|
|
Image Classification (I8)
|
99% |
683
127.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
832
13.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
971
16.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
937
15.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
690
0.84 IPS |
|
|
Pose Estimation (F16)
|
100% |
1131
1.37 IPS |
|
|
Pose Estimation (I8)
|
100% |
1119
1.36 IPS |
|
|
Object Detection (F32)
|
100% |
265
19.8 IPS |
|
|
Object Detection (F16)
|
100% |
390
29.1 IPS |
|
|
Object Detection (I8)
|
62% |
460
34.3 IPS |
|
|
Face Detection (F32)
|
100% |
2084
24.8 IPS |
|
|
Face Detection (F16)
|
97% |
1635
19.4 IPS |
|
|
Face Detection (I8)
|
86% |
1671
19.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
1271
9.86 IPS |
|
|
Depth Estimation (F16)
|
100% |
2697
20.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
2681
20.8 IPS |
|
|
Style Transfer (F32)
|
100% |
3448
4.54 IPS |
|
|
Style Transfer (F16)
|
100% |
6418
8.44 IPS |
|
|
Style Transfer (I8)
|
98% |
7600
10.00 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
385
13.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
256
9.14 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
366
13.1 IPS |
|
|
Text Classification (F32)
|
100% |
429
616.5 IPS |
|
|
Text Classification (F16)
|
100% |
438
629.1 IPS |
|
|
Text Classification (I8)
|
92% |
684
983.2 IPS |
|
|
Machine Translation (F32)
|
100% |
662
12.2 IPS |
|
|
Machine Translation (F16)
|
100% |
638
11.7 IPS |
|
|
Machine Translation (I8)
|
64% |
686
12.6 IPS |
