Samsung Galaxy S23 Ultra
Geekbench ML Score
1078
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 11 2024 04:32 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 Ultra |
| Model ID | samsung SM-S918U |
| 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
662
123.9 IPS |
|
|
Image Classification (F16)
|
100% |
967
180.9 IPS |
|
|
Image Classification (I8)
|
99% |
916
171.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
945
15.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1244
20.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
1074
17.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
969
1.17 IPS |
|
|
Pose Estimation (F16)
|
100% |
1387
1.68 IPS |
|
|
Pose Estimation (I8)
|
100% |
1389
1.68 IPS |
|
|
Object Detection (F32)
|
100% |
348
26.0 IPS |
|
|
Object Detection (F16)
|
100% |
429
32.0 IPS |
|
|
Object Detection (I8)
|
62% |
455
33.9 IPS |
|
|
Face Detection (F32)
|
100% |
2189
26.0 IPS |
|
|
Face Detection (F16)
|
97% |
2152
25.6 IPS |
|
|
Face Detection (I8)
|
86% |
2455
29.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
1504
11.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
2886
22.4 IPS |
|
|
Depth Estimation (I8)
|
95% |
2854
22.1 IPS |
|
|
Style Transfer (F32)
|
100% |
3743
4.92 IPS |
|
|
Style Transfer (F16)
|
100% |
8379
11.0 IPS |
|
|
Style Transfer (I8)
|
98% |
8393
11.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
459
16.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
378
13.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
389
13.9 IPS |
|
|
Text Classification (F32)
|
100% |
428
615.8 IPS |
|
|
Text Classification (F16)
|
100% |
449
645.4 IPS |
|
|
Text Classification (I8)
|
92% |
684
983.6 IPS |
|
|
Machine Translation (F32)
|
100% |
673
12.4 IPS |
|
|
Machine Translation (F16)
|
100% |
651
12.0 IPS |
|
|
Machine Translation (I8)
|
64% |
707
13.0 IPS |
