Samsung Galaxy S23 Ultra
Geekbench ML Score
1124
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 11 2025 10:26 PM |
| Views | 3 |
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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
665
124.4 IPS |
|
|
Image Classification (F16)
|
100% |
1063
198.9 IPS |
|
|
Image Classification (I8)
|
99% |
836
156.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
1118
18.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1518
25.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
1393
23.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
967
1.17 IPS |
|
|
Pose Estimation (F16)
|
100% |
1385
1.68 IPS |
|
|
Pose Estimation (I8)
|
100% |
1388
1.68 IPS |
|
|
Object Detection (F32)
|
100% |
391
29.2 IPS |
|
|
Object Detection (F16)
|
100% |
427
31.9 IPS |
|
|
Object Detection (I8)
|
62% |
282
21.1 IPS |
|
|
Face Detection (F32)
|
100% |
2240
26.6 IPS |
|
|
Face Detection (F16)
|
97% |
3893
46.3 IPS |
|
|
Face Detection (I8)
|
86% |
3633
43.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
1514
11.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
2938
22.8 IPS |
|
|
Depth Estimation (I8)
|
95% |
2893
22.4 IPS |
|
|
Style Transfer (F32)
|
100% |
3789
4.98 IPS |
|
|
Style Transfer (F16)
|
100% |
8596
11.3 IPS |
|
|
Style Transfer (I8)
|
98% |
8559
11.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
479
17.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
395
14.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
396
14.1 IPS |
|
|
Text Classification (F32)
|
100% |
424
609.7 IPS |
|
|
Text Classification (F16)
|
100% |
423
607.6 IPS |
|
|
Text Classification (I8)
|
92% |
600
862.7 IPS |
|
|
Machine Translation (F32)
|
100% |
672
12.4 IPS |
|
|
Machine Translation (F16)
|
100% |
645
11.9 IPS |
|
|
Machine Translation (I8)
|
64% |
695
12.8 IPS |
