Samsung Galaxy S23 Ultra
Geekbench ML Score
558
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 11 2024 01:49 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 Ultra |
| Model ID | samsung SM-S918U |
| 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 | 6.89 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
293
54.8 IPS |
|
|
Image Classification (F16)
|
100% |
274
51.3 IPS |
|
|
Image Classification (I8)
|
97% |
680
127.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
331
5.53 IPS |
|
|
Image Segmentation (F16)
|
100% |
329
5.50 IPS |
|
|
Image Segmentation (I8)
|
98% |
682
11.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
455
0.55 IPS |
|
|
Pose Estimation (F16)
|
100% |
448
0.54 IPS |
|
|
Pose Estimation (I8)
|
100% |
1792
2.17 IPS |
|
|
Object Detection (F32)
|
100% |
275
20.5 IPS |
|
|
Object Detection (F16)
|
100% |
274
20.4 IPS |
|
|
Object Detection (I8)
|
61% |
758
56.6 IPS |
|
|
Face Detection (F32)
|
100% |
649
7.71 IPS |
|
|
Face Detection (F16)
|
100% |
641
7.63 IPS |
|
|
Face Detection (I8)
|
86% |
1484
17.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
572
4.43 IPS |
|
|
Depth Estimation (F16)
|
100% |
571
4.43 IPS |
|
|
Depth Estimation (I8)
|
95% |
1633
12.7 IPS |
|
|
Style Transfer (F32)
|
100% |
913
1.20 IPS |
|
|
Style Transfer (F16)
|
100% |
868
1.14 IPS |
|
|
Style Transfer (I8)
|
98% |
2022
2.66 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
289
10.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
291
10.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1001
35.8 IPS |
|
|
Text Classification (F32)
|
100% |
313
449.5 IPS |
|
|
Text Classification (F16)
|
100% |
312
448.7 IPS |
|
|
Text Classification (I8)
|
92% |
453
650.3 IPS |
|
|
Machine Translation (F32)
|
100% |
543
9.99 IPS |
|
|
Machine Translation (F16)
|
100% |
541
9.96 IPS |
|
|
Machine Translation (I8)
|
64% |
524
9.65 IPS |
