Samsung Galaxy S23 Ultra
Geekbench AI Score
277
Single Precision Score
15974
Half Precision Score
36256
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | clove |
| Upload Date | February 13 2025 09:04 PM |
| Views | 4 |
| Notes | Phone |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| Device | Qualcomm Snapdragon 8 Gen 2 |
| 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 |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
160
29.8 IPS |
|
|
Image Classification (HP)
|
100% |
12418
2.31 KIPS |
|
|
Image Classification (Q)
|
97% |
32178
6.01 KIPS |
|
|
Image Segmentation (SP)
|
100% |
211
3.42 IPS |
|
|
Image Segmentation (HP)
|
100% |
7379
119.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
20888
339.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
287
0.33 IPS |
|
|
Pose Estimation (HP)
|
100% |
72137
84.2 IPS |
|
|
Pose Estimation (Q)
|
98% |
292947
342.9 IPS |
|
|
Object Detection (SP)
|
100% |
158
12.5 IPS |
|
|
Object Detection (HP)
|
100% |
11742
931.4 IPS |
|
|
Object Detection (Q)
|
86% |
13244
1.06 KIPS |
|
|
Face Detection (SP)
|
100% |
443
5.27 IPS |
|
|
Face Detection (HP)
|
100% |
23421
278.3 IPS |
|
|
Face Detection (Q)
|
97% |
81359
970.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
373
2.88 IPS |
|
|
Depth Estimation (HP)
|
99% |
44541
343.2 IPS |
|
|
Depth Estimation (Q)
|
63% |
80692
755.6 IPS |
|
|
Style Transfer (SP)
|
100% |
667
0.86 IPS |
|
|
Style Transfer (HP)
|
98% |
60769
78.4 IPS |
|
|
Style Transfer (Q)
|
98% |
294077
379.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
182
6.70 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
32705
1.21 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
82127
3.04 KIPS |
|
|
Text Classification (SP)
|
100% |
222
296.0 IPS |
|
|
Text Classification (HP)
|
100% |
2504
3.34 KIPS |
|
|
Text Classification (Q)
|
93% |
5644
7.57 KIPS |
|
|
Machine Translation (SP)
|
100% |
391
6.74 IPS |
|
|
Machine Translation (HP)
|
100% |
2686
46.3 IPS |
|
|
Machine Translation (Q)
|
55% |
1682
44.1 IPS |
