Samsung Galaxy S23
Geekbench ML Score
1080
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| User | SebsDaBaws |
| Upload Date | August 20 2024 12:00 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 |
| Model ID | samsung SM-S911B |
| 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% |
660
123.5 IPS |
|
|
Image Classification (F16)
|
100% |
757
141.7 IPS |
|
|
Image Classification (I8)
|
99% |
805
150.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
1057
17.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1324
22.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
1182
19.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
968
1.17 IPS |
|
|
Pose Estimation (F16)
|
100% |
1378
1.67 IPS |
|
|
Pose Estimation (I8)
|
100% |
1384
1.68 IPS |
|
|
Object Detection (F32)
|
100% |
271
20.2 IPS |
|
|
Object Detection (F16)
|
100% |
368
27.5 IPS |
|
|
Object Detection (I8)
|
62% |
486
36.3 IPS |
|
|
Face Detection (F32)
|
100% |
2249
26.7 IPS |
|
|
Face Detection (F16)
|
97% |
2966
35.3 IPS |
|
|
Face Detection (I8)
|
86% |
2428
28.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
1483
11.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
2902
22.5 IPS |
|
|
Depth Estimation (I8)
|
95% |
2869
22.2 IPS |
|
|
Style Transfer (F32)
|
100% |
3766
4.95 IPS |
|
|
Style Transfer (F16)
|
100% |
8548
11.2 IPS |
|
|
Style Transfer (I8)
|
98% |
8527
11.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
472
16.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
392
14.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
392
14.0 IPS |
|
|
Text Classification (F32)
|
100% |
440
632.0 IPS |
|
|
Text Classification (F16)
|
100% |
449
644.7 IPS |
|
|
Text Classification (I8)
|
92% |
684
983.3 IPS |
|
|
Machine Translation (F32)
|
100% |
683
12.6 IPS |
|
|
Machine Translation (F16)
|
100% |
657
12.1 IPS |
|
|
Machine Translation (I8)
|
64% |
718
13.2 IPS |
