Samsung Galaxy S23 Ultra
Geekbench ML Score
1028
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 28 2024 03:53 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
526
98.5 IPS |
|
|
Image Classification (F16)
|
100% |
856
160.1 IPS |
|
|
Image Classification (I8)
|
99% |
777
145.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
912
15.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
1250
20.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
1110
18.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
821
0.99 IPS |
|
|
Pose Estimation (F16)
|
100% |
1276
1.55 IPS |
|
|
Pose Estimation (I8)
|
100% |
1258
1.52 IPS |
|
|
Object Detection (F32)
|
100% |
267
19.9 IPS |
|
|
Object Detection (F16)
|
100% |
395
29.5 IPS |
|
|
Object Detection (I8)
|
62% |
454
33.9 IPS |
|
|
Face Detection (F32)
|
100% |
2189
26.0 IPS |
|
|
Face Detection (F16)
|
97% |
1730
20.6 IPS |
|
|
Face Detection (I8)
|
86% |
2508
29.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
1484
11.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
2870
22.3 IPS |
|
|
Depth Estimation (I8)
|
95% |
2858
22.2 IPS |
|
|
Style Transfer (F32)
|
100% |
3797
5.00 IPS |
|
|
Style Transfer (F16)
|
100% |
8488
11.2 IPS |
|
|
Style Transfer (I8)
|
98% |
8511
11.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
472
16.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
385
13.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
389
13.9 IPS |
|
|
Text Classification (F32)
|
100% |
421
605.3 IPS |
|
|
Text Classification (F16)
|
100% |
432
620.6 IPS |
|
|
Text Classification (I8)
|
92% |
683
981.3 IPS |
|
|
Machine Translation (F32)
|
100% |
665
12.2 IPS |
|
|
Machine Translation (F16)
|
100% |
643
11.8 IPS |
|
|
Machine Translation (I8)
|
64% |
699
12.9 IPS |
