Samsung Galaxy S24 Ultra
Geekbench AI Score
1118
Single Precision Score
1598
Half Precision Score
1522
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| User | giosal |
| Upload Date | August 16 2024 06:25 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 | 10.81 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
786
146.1 IPS |
|
|
Image Classification (HP)
|
100% |
799
148.6 IPS |
|
|
Image Classification (Q)
|
99% |
669
124.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
1375
22.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
1797
29.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
1067
17.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
1116
1.30 IPS |
|
|
Pose Estimation (HP)
|
100% |
2119
2.47 IPS |
|
|
Pose Estimation (Q)
|
96% |
2250
2.64 IPS |
|
|
Object Detection (SP)
|
100% |
607
48.1 IPS |
|
|
Object Detection (HP)
|
100% |
959
76.1 IPS |
|
|
Object Detection (Q)
|
89% |
1019
81.5 IPS |
|
|
Face Detection (SP)
|
100% |
2553
30.3 IPS |
|
|
Face Detection (HP)
|
100% |
2383
28.3 IPS |
|
|
Face Detection (Q)
|
97% |
2336
27.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
1890
14.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
4027
31.0 IPS |
|
|
Depth Estimation (Q)
|
74% |
3737
30.5 IPS |
|
|
Style Transfer (SP)
|
100% |
6566
8.44 IPS |
|
|
Style Transfer (HP)
|
100% |
9499
12.2 IPS |
|
|
Style Transfer (Q)
|
98% |
8578
11.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
438
16.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1361
50.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1362
50.5 IPS |
|
|
Text Classification (SP)
|
100% |
431
575.2 IPS |
|
|
Text Classification (HP)
|
100% |
431
575.7 IPS |
|
|
Text Classification (Q)
|
91% |
678
911.0 IPS |
|
|
Machine Translation (SP)
|
100% |
697
12.0 IPS |
|
|
Machine Translation (HP)
|
100% |
698
12.0 IPS |
|
|
Machine Translation (Q)
|
57% |
592
14.5 IPS |
