Samsung Galaxy S23
Geekbench ML Score
405
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 26 2025 07:19 AM |
| Views | 7 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 |
| Model ID | samsung SM-S9110 |
| 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% |
248
46.3 IPS |
|
|
Image Classification (F16)
|
100% |
248
46.5 IPS |
|
|
Image Classification (I8)
|
97% |
564
105.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
284
4.75 IPS |
|
|
Image Segmentation (F16)
|
100% |
269
4.50 IPS |
|
|
Image Segmentation (I8)
|
98% |
484
8.09 IPS |
|
|
Pose Estimation (F32)
|
100% |
358
0.43 IPS |
|
|
Pose Estimation (F16)
|
100% |
335
0.41 IPS |
|
|
Pose Estimation (I8)
|
100% |
1184
1.43 IPS |
|
|
Object Detection (F32)
|
100% |
178
13.3 IPS |
|
|
Object Detection (F16)
|
100% |
176
13.2 IPS |
|
|
Object Detection (I8)
|
61% |
445
33.2 IPS |
|
|
Face Detection (F32)
|
100% |
445
5.29 IPS |
|
|
Face Detection (F16)
|
100% |
447
5.32 IPS |
|
|
Face Detection (I8)
|
86% |
883
10.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
385
2.99 IPS |
|
|
Depth Estimation (F16)
|
100% |
394
3.05 IPS |
|
|
Depth Estimation (I8)
|
95% |
975
7.56 IPS |
|
|
Style Transfer (F32)
|
100% |
637
0.84 IPS |
|
|
Style Transfer (F16)
|
100% |
633
0.83 IPS |
|
|
Style Transfer (I8)
|
98% |
1482
1.95 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
205
7.33 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
207
7.39 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
715
25.5 IPS |
|
|
Text Classification (F32)
|
100% |
240
345.2 IPS |
|
|
Text Classification (F16)
|
100% |
237
341.2 IPS |
|
|
Text Classification (I8)
|
92% |
347
498.9 IPS |
|
|
Machine Translation (F32)
|
100% |
424
7.80 IPS |
|
|
Machine Translation (F16)
|
100% |
424
7.80 IPS |
|
|
Machine Translation (I8)
|
64% |
401
7.37 IPS |
