Samsung Galaxy S23 Plus
Geekbench ML Score
837
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 01:26 PM |
| Views | 4 |
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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
433
81.1 IPS |
|
|
Image Classification (F16)
|
100% |
446
83.5 IPS |
|
|
Image Classification (I8)
|
97% |
776
145.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
596
9.95 IPS |
|
|
Image Segmentation (F16)
|
100% |
592
9.88 IPS |
|
|
Image Segmentation (I8)
|
98% |
719
12.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
1075
1.30 IPS |
|
|
Pose Estimation (F16)
|
100% |
1084
1.31 IPS |
|
|
Pose Estimation (I8)
|
100% |
4783
5.79 IPS |
|
|
Object Detection (F32)
|
100% |
473
35.3 IPS |
|
|
Object Detection (F16)
|
100% |
462
34.5 IPS |
|
|
Object Detection (I8)
|
61% |
1077
80.4 IPS |
|
|
Face Detection (F32)
|
100% |
1005
11.9 IPS |
|
|
Face Detection (F16)
|
100% |
929
11.0 IPS |
|
|
Face Detection (I8)
|
86% |
1710
20.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
940
7.29 IPS |
|
|
Depth Estimation (F16)
|
100% |
914
7.09 IPS |
|
|
Depth Estimation (I8)
|
95% |
1510
11.7 IPS |
|
|
Style Transfer (F32)
|
100% |
1835
2.41 IPS |
|
|
Style Transfer (F16)
|
100% |
1789
2.35 IPS |
|
|
Style Transfer (I8)
|
98% |
3542
4.66 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
573
20.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
567
20.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1362
48.6 IPS |
|
|
Text Classification (F32)
|
100% |
364
523.0 IPS |
|
|
Text Classification (F16)
|
100% |
374
537.3 IPS |
|
|
Text Classification (I8)
|
92% |
237
340.0 IPS |
|
|
Machine Translation (F32)
|
100% |
755
13.9 IPS |
|
|
Machine Translation (F16)
|
100% |
966
17.8 IPS |
|
|
Machine Translation (I8)
|
64% |
388
7.15 IPS |
