Samsung Galaxy S23 Ultra
Geekbench ML Score
592
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 11 2025 10:33 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% |
277
51.8 IPS |
|
|
Image Classification (F16)
|
100% |
267
49.9 IPS |
|
|
Image Classification (I8)
|
97% |
689
128.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
326
5.44 IPS |
|
|
Image Segmentation (F16)
|
100% |
324
5.41 IPS |
|
|
Image Segmentation (I8)
|
98% |
684
11.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
451
0.55 IPS |
|
|
Pose Estimation (F16)
|
100% |
447
0.54 IPS |
|
|
Pose Estimation (I8)
|
100% |
1835
2.22 IPS |
|
|
Object Detection (F32)
|
100% |
285
21.3 IPS |
|
|
Object Detection (F16)
|
100% |
286
21.3 IPS |
|
|
Object Detection (I8)
|
61% |
797
59.5 IPS |
|
|
Face Detection (F32)
|
100% |
652
7.75 IPS |
|
|
Face Detection (F16)
|
100% |
634
7.54 IPS |
|
|
Face Detection (I8)
|
86% |
1469
17.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
553
4.29 IPS |
|
|
Depth Estimation (F16)
|
100% |
561
4.35 IPS |
|
|
Depth Estimation (I8)
|
95% |
1639
12.7 IPS |
|
|
Style Transfer (F32)
|
100% |
900
1.18 IPS |
|
|
Style Transfer (F16)
|
100% |
889
1.17 IPS |
|
|
Style Transfer (I8)
|
98% |
2266
2.98 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
324
11.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
323
11.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1156
41.3 IPS |
|
|
Text Classification (F32)
|
100% |
405
581.7 IPS |
|
|
Text Classification (F16)
|
100% |
407
584.8 IPS |
|
|
Text Classification (I8)
|
92% |
599
861.2 IPS |
|
|
Machine Translation (F32)
|
100% |
629
11.6 IPS |
|
|
Machine Translation (F16)
|
100% |
614
11.3 IPS |
|
|
Machine Translation (I8)
|
64% |
676
12.4 IPS |
