Samsung Galaxy S23
Geekbench ML Score
410
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 10:29 AM |
| 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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
210
39.3 IPS |
|
|
Image Classification (F16)
|
100% |
210
39.3 IPS |
|
|
Image Classification (I8)
|
97% |
467
87.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
231
3.86 IPS |
|
|
Image Segmentation (F16)
|
100% |
232
3.88 IPS |
|
|
Image Segmentation (I8)
|
98% |
447
7.46 IPS |
|
|
Pose Estimation (F32)
|
100% |
332
0.40 IPS |
|
|
Pose Estimation (F16)
|
100% |
328
0.40 IPS |
|
|
Pose Estimation (I8)
|
100% |
1276
1.54 IPS |
|
|
Object Detection (F32)
|
100% |
194
14.5 IPS |
|
|
Object Detection (F16)
|
100% |
184
13.8 IPS |
|
|
Object Detection (I8)
|
61% |
506
37.8 IPS |
|
|
Face Detection (F32)
|
100% |
472
5.62 IPS |
|
|
Face Detection (F16)
|
100% |
470
5.59 IPS |
|
|
Face Detection (I8)
|
86% |
941
11.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
399
3.10 IPS |
|
|
Depth Estimation (F16)
|
100% |
415
3.22 IPS |
|
|
Depth Estimation (I8)
|
95% |
1083
8.40 IPS |
|
|
Style Transfer (F32)
|
100% |
669
0.88 IPS |
|
|
Style Transfer (F16)
|
100% |
676
0.89 IPS |
|
|
Style Transfer (I8)
|
98% |
1600
2.10 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
223
7.95 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
219
7.81 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
754
26.9 IPS |
|
|
Text Classification (F32)
|
100% |
256
367.7 IPS |
|
|
Text Classification (F16)
|
100% |
257
368.8 IPS |
|
|
Text Classification (I8)
|
92% |
373
535.7 IPS |
|
|
Machine Translation (F32)
|
100% |
445
8.19 IPS |
|
|
Machine Translation (F16)
|
100% |
449
8.26 IPS |
|
|
Machine Translation (I8)
|
64% |
400
7.37 IPS |
