Samsung Galaxy S23 Ultra
Geekbench ML Score
614
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 28 2024 03:56 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 Ultra |
| Model ID | samsung SM-S918N |
| 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% |
284
53.2 IPS |
|
|
Image Classification (F16)
|
100% |
274
51.3 IPS |
|
|
Image Classification (I8)
|
97% |
689
129.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
338
5.65 IPS |
|
|
Image Segmentation (F16)
|
100% |
340
5.68 IPS |
|
|
Image Segmentation (I8)
|
98% |
712
11.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
472
0.57 IPS |
|
|
Pose Estimation (F16)
|
100% |
466
0.56 IPS |
|
|
Pose Estimation (I8)
|
100% |
1909
2.31 IPS |
|
|
Object Detection (F32)
|
100% |
289
21.6 IPS |
|
|
Object Detection (F16)
|
100% |
291
21.7 IPS |
|
|
Object Detection (I8)
|
61% |
805
60.1 IPS |
|
|
Face Detection (F32)
|
100% |
678
8.06 IPS |
|
|
Face Detection (F16)
|
100% |
666
7.91 IPS |
|
|
Face Detection (I8)
|
86% |
1503
17.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
588
4.56 IPS |
|
|
Depth Estimation (F16)
|
100% |
587
4.55 IPS |
|
|
Depth Estimation (I8)
|
95% |
1664
12.9 IPS |
|
|
Style Transfer (F32)
|
100% |
953
1.25 IPS |
|
|
Style Transfer (F16)
|
100% |
946
1.24 IPS |
|
|
Style Transfer (I8)
|
98% |
2448
3.22 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
334
11.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
337
12.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1164
41.6 IPS |
|
|
Text Classification (F32)
|
100% |
410
589.4 IPS |
|
|
Text Classification (F16)
|
100% |
417
599.2 IPS |
|
|
Text Classification (I8)
|
92% |
654
939.4 IPS |
|
|
Machine Translation (F32)
|
100% |
650
12.0 IPS |
|
|
Machine Translation (F16)
|
100% |
632
11.6 IPS |
|
|
Machine Translation (I8)
|
64% |
698
12.9 IPS |
