Samsung Galaxy S23
Geekbench ML Score
626
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 31 2024 10:08 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 |
| Model ID | samsung SM-S911N |
| 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% |
294
55.0 IPS |
|
|
Image Classification (F16)
|
100% |
288
53.9 IPS |
|
|
Image Classification (I8)
|
97% |
720
134.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
355
5.93 IPS |
|
|
Image Segmentation (F16)
|
100% |
355
5.93 IPS |
|
|
Image Segmentation (I8)
|
98% |
728
12.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
486
0.59 IPS |
|
|
Pose Estimation (F16)
|
100% |
482
0.58 IPS |
|
|
Pose Estimation (I8)
|
100% |
2030
2.46 IPS |
|
|
Object Detection (F32)
|
100% |
298
22.2 IPS |
|
|
Object Detection (F16)
|
100% |
301
22.5 IPS |
|
|
Object Detection (I8)
|
61% |
836
62.4 IPS |
|
|
Face Detection (F32)
|
100% |
689
8.19 IPS |
|
|
Face Detection (F16)
|
100% |
678
8.07 IPS |
|
|
Face Detection (I8)
|
86% |
1560
18.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
601
4.66 IPS |
|
|
Depth Estimation (F16)
|
100% |
606
4.70 IPS |
|
|
Depth Estimation (I8)
|
95% |
1724
13.4 IPS |
|
|
Style Transfer (F32)
|
100% |
950
1.25 IPS |
|
|
Style Transfer (F16)
|
100% |
962
1.27 IPS |
|
|
Style Transfer (I8)
|
98% |
2382
3.13 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
343
12.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
315
11.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1246
44.5 IPS |
|
|
Text Classification (F32)
|
100% |
423
607.5 IPS |
|
|
Text Classification (F16)
|
100% |
422
606.9 IPS |
|
|
Text Classification (I8)
|
92% |
579
831.7 IPS |
|
|
Machine Translation (F32)
|
100% |
655
12.1 IPS |
|
|
Machine Translation (F16)
|
100% |
671
12.3 IPS |
|
|
Machine Translation (I8)
|
64% |
673
12.4 IPS |
