Samsung Galaxy S23 Ultra
Geekbench ML Score
1047
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 07 2024 06:55 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 Ultra |
| Model ID | samsung SM-S918W |
| 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
658
123.1 IPS |
|
|
Image Classification (F16)
|
100% |
845
158.1 IPS |
|
|
Image Classification (I8)
|
99% |
684
128.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
855
14.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
974
16.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
946
15.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
965
1.17 IPS |
|
|
Pose Estimation (F16)
|
100% |
1380
1.67 IPS |
|
|
Pose Estimation (I8)
|
100% |
1392
1.69 IPS |
|
|
Object Detection (F32)
|
100% |
359
26.8 IPS |
|
|
Object Detection (F16)
|
100% |
432
32.2 IPS |
|
|
Object Detection (I8)
|
62% |
463
34.6 IPS |
|
|
Face Detection (F32)
|
100% |
2291
27.2 IPS |
|
|
Face Detection (F16)
|
97% |
2677
31.8 IPS |
|
|
Face Detection (I8)
|
86% |
2356
28.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
1499
11.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
2891
22.4 IPS |
|
|
Depth Estimation (I8)
|
95% |
2832
22.0 IPS |
|
|
Style Transfer (F32)
|
100% |
3270
4.30 IPS |
|
|
Style Transfer (F16)
|
100% |
8498
11.2 IPS |
|
|
Style Transfer (I8)
|
98% |
8297
10.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
471
16.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
389
13.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
387
13.8 IPS |
|
|
Text Classification (F32)
|
100% |
418
600.7 IPS |
|
|
Text Classification (F16)
|
100% |
418
600.7 IPS |
|
|
Text Classification (I8)
|
92% |
680
977.4 IPS |
|
|
Machine Translation (F32)
|
100% |
658
12.1 IPS |
|
|
Machine Translation (F16)
|
100% |
642
11.8 IPS |
|
|
Machine Translation (I8)
|
64% |
687
12.6 IPS |
