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 | February 11 2025 10:30 PM |
| Views | 3 |
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% |
282
52.8 IPS |
|
|
Image Classification (F16)
|
100% |
268
50.1 IPS |
|
|
Image Classification (I8)
|
97% |
700
130.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
329
5.50 IPS |
|
|
Image Segmentation (F16)
|
100% |
329
5.50 IPS |
|
|
Image Segmentation (I8)
|
98% |
692
11.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
458
0.55 IPS |
|
|
Pose Estimation (F16)
|
100% |
454
0.55 IPS |
|
|
Pose Estimation (I8)
|
100% |
1920
2.33 IPS |
|
|
Object Detection (F32)
|
100% |
291
21.7 IPS |
|
|
Object Detection (F16)
|
100% |
296
22.1 IPS |
|
|
Object Detection (I8)
|
61% |
807
60.3 IPS |
|
|
Face Detection (F32)
|
100% |
658
7.83 IPS |
|
|
Face Detection (F16)
|
100% |
647
7.69 IPS |
|
|
Face Detection (I8)
|
86% |
1440
17.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
571
4.43 IPS |
|
|
Depth Estimation (F16)
|
100% |
577
4.48 IPS |
|
|
Depth Estimation (I8)
|
95% |
1683
13.0 IPS |
|
|
Style Transfer (F32)
|
100% |
895
1.18 IPS |
|
|
Style Transfer (F16)
|
100% |
903
1.19 IPS |
|
|
Style Transfer (I8)
|
98% |
2273
2.99 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
330
11.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
325
11.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1166
41.6 IPS |
|
|
Text Classification (F32)
|
100% |
408
586.1 IPS |
|
|
Text Classification (F16)
|
100% |
416
597.5 IPS |
|
|
Text Classification (I8)
|
92% |
601
863.6 IPS |
|
|
Machine Translation (F32)
|
100% |
642
11.8 IPS |
|
|
Machine Translation (F16)
|
100% |
613
11.3 IPS |
|
|
Machine Translation (I8)
|
64% |
679
12.5 IPS |
