Samsung Galaxy S23 Ultra
Geekbench ML Score
584
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 01 2024 07:48 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 Ultra |
| Model ID | samsung SM-S918B |
| 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 | 10.77 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
277
51.8 IPS |
|
|
Image Classification (F16)
|
100% |
266
49.7 IPS |
|
|
Image Classification (I8)
|
97% |
660
123.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
325
5.42 IPS |
|
|
Image Segmentation (F16)
|
100% |
322
5.37 IPS |
|
|
Image Segmentation (I8)
|
98% |
677
11.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
447
0.54 IPS |
|
|
Pose Estimation (F16)
|
100% |
443
0.54 IPS |
|
|
Pose Estimation (I8)
|
100% |
1752
2.12 IPS |
|
|
Object Detection (F32)
|
100% |
275
20.5 IPS |
|
|
Object Detection (F16)
|
100% |
282
21.1 IPS |
|
|
Object Detection (I8)
|
61% |
766
57.2 IPS |
|
|
Face Detection (F32)
|
100% |
636
7.57 IPS |
|
|
Face Detection (F16)
|
100% |
625
7.43 IPS |
|
|
Face Detection (I8)
|
86% |
1422
16.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
556
4.31 IPS |
|
|
Depth Estimation (F16)
|
100% |
550
4.27 IPS |
|
|
Depth Estimation (I8)
|
95% |
1607
12.5 IPS |
|
|
Style Transfer (F32)
|
100% |
894
1.18 IPS |
|
|
Style Transfer (F16)
|
100% |
888
1.17 IPS |
|
|
Style Transfer (I8)
|
98% |
2262
2.98 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
324
11.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
312
11.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1114
39.8 IPS |
|
|
Text Classification (F32)
|
100% |
397
571.2 IPS |
|
|
Text Classification (F16)
|
100% |
409
588.2 IPS |
|
|
Text Classification (I8)
|
92% |
627
901.3 IPS |
|
|
Machine Translation (F32)
|
100% |
618
11.4 IPS |
|
|
Machine Translation (F16)
|
100% |
609
11.2 IPS |
|
|
Machine Translation (I8)
|
64% |
667
12.3 IPS |
