Samsung Galaxy S24 Ultra
Geekbench AI Score
463
Single Precision Score
462
Half Precision Score
1009
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 09 2025 11:01 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S24 Ultra |
| Model ID | samsung SM-S928U1 |
| Motherboard | pineapple |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.40 GHz |
| Memory Information | |
|---|---|
| Size | 10.83 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
311
57.9 IPS |
|
|
Image Classification (HP)
|
100% |
314
58.5 IPS |
|
|
Image Classification (Q)
|
99% |
813
151.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
397
6.43 IPS |
|
|
Image Segmentation (HP)
|
100% |
403
6.54 IPS |
|
|
Image Segmentation (Q)
|
98% |
810
13.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
554
0.65 IPS |
|
|
Pose Estimation (HP)
|
100% |
537
0.63 IPS |
|
|
Pose Estimation (Q)
|
98% |
2075
2.43 IPS |
|
|
Object Detection (SP)
|
100% |
297
23.6 IPS |
|
|
Object Detection (HP)
|
100% |
294
23.3 IPS |
|
|
Object Detection (Q)
|
87% |
747
59.9 IPS |
|
|
Face Detection (SP)
|
100% |
680
8.08 IPS |
|
|
Face Detection (HP)
|
100% |
690
8.20 IPS |
|
|
Face Detection (Q)
|
97% |
1534
18.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
582
4.49 IPS |
|
|
Depth Estimation (HP)
|
99% |
561
4.32 IPS |
|
|
Depth Estimation (Q)
|
64% |
1236
11.2 IPS |
|
|
Style Transfer (SP)
|
100% |
905
1.16 IPS |
|
|
Style Transfer (HP)
|
100% |
863
1.11 IPS |
|
|
Style Transfer (Q)
|
98% |
2019
2.60 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
287
10.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
294
10.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
962
35.6 IPS |
|
|
Text Classification (SP)
|
100% |
352
470.3 IPS |
|
|
Text Classification (HP)
|
100% |
368
490.7 IPS |
|
|
Text Classification (Q)
|
91% |
601
808.1 IPS |
|
|
Machine Translation (SP)
|
100% |
623
10.7 IPS |
|
|
Machine Translation (HP)
|
100% |
615
10.6 IPS |
|
|
Machine Translation (Q)
|
57% |
486
11.9 IPS |
