Samsung Galaxy S23 Ultra
Geekbench ML Score
1096
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | June 15 2025 06:23 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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 | 10.79 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
666
124.6 IPS |
|
|
Image Classification (F16)
|
100% |
776
145.2 IPS |
|
|
Image Classification (I8)
|
99% |
830
155.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
1120
18.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1518
25.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
1290
21.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
969
1.17 IPS |
|
|
Pose Estimation (F16)
|
100% |
1392
1.69 IPS |
|
|
Pose Estimation (I8)
|
100% |
1389
1.68 IPS |
|
|
Object Detection (F32)
|
100% |
333
24.8 IPS |
|
|
Object Detection (F16)
|
100% |
388
29.0 IPS |
|
|
Object Detection (I8)
|
62% |
447
33.4 IPS |
|
|
Face Detection (F32)
|
100% |
2242
26.7 IPS |
|
|
Face Detection (F16)
|
97% |
2320
27.6 IPS |
|
|
Face Detection (I8)
|
86% |
2924
34.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
1483
11.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
2881
22.3 IPS |
|
|
Depth Estimation (I8)
|
95% |
2839
22.0 IPS |
|
|
Style Transfer (F32)
|
100% |
3775
4.97 IPS |
|
|
Style Transfer (F16)
|
100% |
8505
11.2 IPS |
|
|
Style Transfer (I8)
|
98% |
8473
11.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
455
16.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
387
13.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
385
13.8 IPS |
|
|
Text Classification (F32)
|
100% |
453
650.8 IPS |
|
|
Text Classification (F16)
|
100% |
447
642.4 IPS |
|
|
Text Classification (I8)
|
92% |
685
984.6 IPS |
|
|
Machine Translation (F32)
|
100% |
685
12.6 IPS |
|
|
Machine Translation (F16)
|
100% |
663
12.2 IPS |
|
|
Machine Translation (I8)
|
64% |
727
13.4 IPS |
