Samsung Galaxy S24 Ultra
Geekbench AI Score
1175
Single Precision Score
1695
Half Precision Score
1691
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | mersa |
| Upload Date | January 28 2025 05:47 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S24 Ultra |
| Model ID | samsung SM-S928B |
| 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% |
816
151.8 IPS |
|
|
Image Classification (HP)
|
100% |
590
109.7 IPS |
|
|
Image Classification (Q)
|
96% |
829
154.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1287
20.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
1987
32.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
1491
24.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
1111
1.30 IPS |
|
|
Pose Estimation (HP)
|
100% |
2720
3.17 IPS |
|
|
Pose Estimation (Q)
|
96% |
2716
3.18 IPS |
|
|
Object Detection (SP)
|
100% |
696
55.2 IPS |
|
|
Object Detection (HP)
|
100% |
740
58.7 IPS |
|
|
Object Detection (Q)
|
87% |
905
72.7 IPS |
|
|
Face Detection (SP)
|
100% |
2655
31.6 IPS |
|
|
Face Detection (HP)
|
100% |
3562
42.3 IPS |
|
|
Face Detection (Q)
|
97% |
2326
27.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
1878
14.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
3975
30.7 IPS |
|
|
Depth Estimation (Q)
|
63% |
3272
30.3 IPS |
|
|
Style Transfer (SP)
|
100% |
7346
9.44 IPS |
|
|
Style Transfer (HP)
|
100% |
11833
15.2 IPS |
|
|
Style Transfer (Q)
|
98% |
11767
15.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
542
20.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1593
58.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1584
58.7 IPS |
|
|
Text Classification (SP)
|
100% |
446
595.8 IPS |
|
|
Text Classification (HP)
|
100% |
457
609.8 IPS |
|
|
Text Classification (Q)
|
91% |
746
1.00 KIPS |
|
|
Machine Translation (SP)
|
100% |
700
12.1 IPS |
|
|
Machine Translation (HP)
|
100% |
684
11.8 IPS |
|
|
Machine Translation (Q)
|
57% |
596
14.6 IPS |
