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 | March 28 2024 04:19 PM |
| 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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
285
53.4 IPS |
|
|
Image Classification (F16)
|
100% |
276
51.6 IPS |
|
|
Image Classification (I8)
|
97% |
681
127.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
336
5.61 IPS |
|
|
Image Segmentation (F16)
|
100% |
336
5.61 IPS |
|
|
Image Segmentation (I8)
|
98% |
693
11.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
465
0.56 IPS |
|
|
Pose Estimation (F16)
|
100% |
457
0.55 IPS |
|
|
Pose Estimation (I8)
|
100% |
1915
2.32 IPS |
|
|
Object Detection (F32)
|
100% |
288
21.5 IPS |
|
|
Object Detection (F16)
|
100% |
288
21.5 IPS |
|
|
Object Detection (I8)
|
61% |
789
58.9 IPS |
|
|
Face Detection (F32)
|
100% |
659
7.83 IPS |
|
|
Face Detection (F16)
|
100% |
651
7.74 IPS |
|
|
Face Detection (I8)
|
86% |
1478
17.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
575
4.46 IPS |
|
|
Depth Estimation (F16)
|
100% |
574
4.45 IPS |
|
|
Depth Estimation (I8)
|
95% |
1593
12.3 IPS |
|
|
Style Transfer (F32)
|
100% |
916
1.20 IPS |
|
|
Style Transfer (F16)
|
100% |
922
1.21 IPS |
|
|
Style Transfer (I8)
|
98% |
2305
3.03 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
326
11.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
324
11.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1146
40.9 IPS |
|
|
Text Classification (F32)
|
100% |
403
579.1 IPS |
|
|
Text Classification (F16)
|
100% |
409
587.9 IPS |
|
|
Text Classification (I8)
|
92% |
632
908.0 IPS |
|
|
Machine Translation (F32)
|
100% |
637
11.7 IPS |
|
|
Machine Translation (F16)
|
100% |
617
11.4 IPS |
|
|
Machine Translation (I8)
|
64% |
676
12.4 IPS |
