Samsung Galaxy S23 Ultra
Geekbench ML Score
538
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 20 2024 04:51 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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
283
52.9 IPS |
|
|
Image Classification (F16)
|
100% |
273
51.1 IPS |
|
|
Image Classification (I8)
|
97% |
691
129.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
331
5.53 IPS |
|
|
Image Segmentation (F16)
|
100% |
329
5.49 IPS |
|
|
Image Segmentation (I8)
|
98% |
688
11.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
451
0.55 IPS |
|
|
Pose Estimation (F16)
|
100% |
449
0.54 IPS |
|
|
Pose Estimation (I8)
|
100% |
1968
2.38 IPS |
|
|
Object Detection (F32)
|
100% |
269
20.1 IPS |
|
|
Object Detection (F16)
|
100% |
269
20.1 IPS |
|
|
Object Detection (I8)
|
61% |
685
51.1 IPS |
|
|
Face Detection (F32)
|
100% |
641
7.62 IPS |
|
|
Face Detection (F16)
|
100% |
622
7.40 IPS |
|
|
Face Detection (I8)
|
86% |
1245
14.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
519
4.02 IPS |
|
|
Depth Estimation (F16)
|
100% |
520
4.03 IPS |
|
|
Depth Estimation (I8)
|
95% |
1336
10.4 IPS |
|
|
Style Transfer (F32)
|
100% |
808
1.06 IPS |
|
|
Style Transfer (F16)
|
100% |
811
1.07 IPS |
|
|
Style Transfer (I8)
|
98% |
1886
2.48 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
273
9.75 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
275
9.82 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
946
33.8 IPS |
|
|
Text Classification (F32)
|
100% |
312
447.8 IPS |
|
|
Text Classification (F16)
|
100% |
312
448.1 IPS |
|
|
Text Classification (I8)
|
92% |
452
649.9 IPS |
|
|
Machine Translation (F32)
|
100% |
545
10.0 IPS |
|
|
Machine Translation (F16)
|
100% |
563
10.4 IPS |
|
|
Machine Translation (I8)
|
64% |
520
9.56 IPS |
