Samsung Galaxy S23 Ultra
Geekbench ML Score
601
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 20 2024 05:33 AM |
| Views | 2 |
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% |
274
51.4 IPS |
|
|
Image Classification (F16)
|
100% |
271
50.7 IPS |
|
|
Image Classification (I8)
|
97% |
683
127.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
331
5.54 IPS |
|
|
Image Segmentation (F16)
|
100% |
327
5.47 IPS |
|
|
Image Segmentation (I8)
|
98% |
689
11.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
456
0.55 IPS |
|
|
Pose Estimation (F16)
|
100% |
453
0.55 IPS |
|
|
Pose Estimation (I8)
|
100% |
1936
2.34 IPS |
|
|
Object Detection (F32)
|
100% |
288
21.5 IPS |
|
|
Object Detection (F16)
|
100% |
287
21.4 IPS |
|
|
Object Detection (I8)
|
61% |
807
60.3 IPS |
|
|
Face Detection (F32)
|
100% |
656
7.80 IPS |
|
|
Face Detection (F16)
|
100% |
642
7.64 IPS |
|
|
Face Detection (I8)
|
86% |
1472
17.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
569
4.42 IPS |
|
|
Depth Estimation (F16)
|
100% |
568
4.40 IPS |
|
|
Depth Estimation (I8)
|
95% |
1639
12.7 IPS |
|
|
Style Transfer (F32)
|
100% |
897
1.18 IPS |
|
|
Style Transfer (F16)
|
100% |
905
1.19 IPS |
|
|
Style Transfer (I8)
|
98% |
2355
3.10 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
333
11.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
325
11.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1149
41.0 IPS |
|
|
Text Classification (F32)
|
100% |
418
600.1 IPS |
|
|
Text Classification (F16)
|
100% |
410
589.3 IPS |
|
|
Text Classification (I8)
|
92% |
648
931.9 IPS |
|
|
Machine Translation (F32)
|
100% |
638
11.7 IPS |
|
|
Machine Translation (F16)
|
100% |
619
11.4 IPS |
|
|
Machine Translation (I8)
|
64% |
677
12.5 IPS |
