Samsung Galaxy S23 Plus
Geekbench ML Score
1206
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 01:33 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 Plus |
| Model ID | samsung SM-S916B |
| 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% |
662
123.9 IPS |
|
|
Image Classification (F16)
|
100% |
1092
204.4 IPS |
|
|
Image Classification (I8)
|
99% |
967
181.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
1320
22.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
2079
34.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
1885
31.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
970
1.17 IPS |
|
|
Pose Estimation (F16)
|
100% |
1376
1.67 IPS |
|
|
Pose Estimation (I8)
|
100% |
1383
1.67 IPS |
|
|
Object Detection (F32)
|
100% |
465
34.7 IPS |
|
|
Object Detection (F16)
|
100% |
612
45.7 IPS |
|
|
Object Detection (I8)
|
62% |
605
45.2 IPS |
|
|
Face Detection (F32)
|
100% |
2317
27.6 IPS |
|
|
Face Detection (F16)
|
97% |
3705
44.0 IPS |
|
|
Face Detection (I8)
|
86% |
3236
38.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
1513
11.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
2926
22.7 IPS |
|
|
Depth Estimation (I8)
|
95% |
2898
22.5 IPS |
|
|
Style Transfer (F32)
|
100% |
3793
4.99 IPS |
|
|
Style Transfer (F16)
|
100% |
8606
11.3 IPS |
|
|
Style Transfer (I8)
|
98% |
8559
11.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
479
17.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
397
14.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
394
14.1 IPS |
|
|
Text Classification (F32)
|
100% |
422
607.1 IPS |
|
|
Text Classification (F16)
|
100% |
423
607.5 IPS |
|
|
Text Classification (I8)
|
92% |
603
866.1 IPS |
|
|
Machine Translation (F32)
|
100% |
668
12.3 IPS |
|
|
Machine Translation (F16)
|
100% |
641
11.8 IPS |
|
|
Machine Translation (I8)
|
64% |
699
12.9 IPS |
