Samsung Galaxy S23 Ultra
Geekbench ML Score
1055
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 11 2024 01:43 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
659
123.2 IPS |
|
|
Image Classification (F16)
|
100% |
855
160.0 IPS |
|
|
Image Classification (I8)
|
99% |
736
137.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
910
15.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
1152
19.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
960
16.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
961
1.16 IPS |
|
|
Pose Estimation (F16)
|
100% |
1386
1.68 IPS |
|
|
Pose Estimation (I8)
|
100% |
1388
1.68 IPS |
|
|
Object Detection (F32)
|
100% |
268
20.0 IPS |
|
|
Object Detection (F16)
|
100% |
432
32.3 IPS |
|
|
Object Detection (I8)
|
62% |
408
30.5 IPS |
|
|
Face Detection (F32)
|
100% |
2204
26.2 IPS |
|
|
Face Detection (F16)
|
97% |
3064
36.4 IPS |
|
|
Face Detection (I8)
|
86% |
2809
33.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1492
11.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
2903
22.5 IPS |
|
|
Depth Estimation (I8)
|
95% |
2882
22.3 IPS |
|
|
Style Transfer (F32)
|
100% |
3803
5.00 IPS |
|
|
Style Transfer (F16)
|
100% |
8483
11.2 IPS |
|
|
Style Transfer (I8)
|
98% |
8537
11.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
467
16.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
386
13.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
390
13.9 IPS |
|
|
Text Classification (F32)
|
100% |
407
585.3 IPS |
|
|
Text Classification (F16)
|
100% |
412
592.0 IPS |
|
|
Text Classification (I8)
|
92% |
652
937.5 IPS |
|
|
Machine Translation (F32)
|
100% |
652
12.0 IPS |
|
|
Machine Translation (F16)
|
100% |
625
11.5 IPS |
|
|
Machine Translation (I8)
|
64% |
676
12.4 IPS |
