Samsung Galaxy S23
Geekbench ML Score
477
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| User | SebsDaBaws |
| Upload Date | August 20 2024 11:50 AM |
| Views | 3 |
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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
256
48.0 IPS |
|
|
Image Classification (F16)
|
100% |
248
46.5 IPS |
|
|
Image Classification (I8)
|
97% |
585
109.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
299
4.99 IPS |
|
|
Image Segmentation (F16)
|
100% |
298
4.98 IPS |
|
|
Image Segmentation (I8)
|
98% |
546
9.12 IPS |
|
|
Pose Estimation (F32)
|
100% |
405
0.49 IPS |
|
|
Pose Estimation (F16)
|
100% |
405
0.49 IPS |
|
|
Pose Estimation (I8)
|
100% |
1603
1.94 IPS |
|
|
Object Detection (F32)
|
100% |
241
18.0 IPS |
|
|
Object Detection (F16)
|
100% |
224
16.7 IPS |
|
|
Object Detection (I8)
|
61% |
570
42.6 IPS |
|
|
Face Detection (F32)
|
100% |
530
6.31 IPS |
|
|
Face Detection (F16)
|
100% |
541
6.44 IPS |
|
|
Face Detection (I8)
|
86% |
1071
12.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
450
3.49 IPS |
|
|
Depth Estimation (F16)
|
100% |
445
3.45 IPS |
|
|
Depth Estimation (I8)
|
95% |
1164
9.03 IPS |
|
|
Style Transfer (F32)
|
100% |
730
0.96 IPS |
|
|
Style Transfer (F16)
|
100% |
762
1.00 IPS |
|
|
Style Transfer (I8)
|
98% |
1684
2.22 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
243
8.69 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
240
8.59 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
828
29.6 IPS |
|
|
Text Classification (F32)
|
100% |
294
421.8 IPS |
|
|
Text Classification (F16)
|
100% |
294
422.8 IPS |
|
|
Text Classification (I8)
|
92% |
420
603.8 IPS |
|
|
Machine Translation (F32)
|
100% |
508
9.36 IPS |
|
|
Machine Translation (F16)
|
100% |
537
9.88 IPS |
|
|
Machine Translation (I8)
|
64% |
489
8.99 IPS |
