Samsung Galaxy S24 Ultra
Geekbench AI Score
2474
Single Precision Score
2516
Half Precision Score
3623
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| User | giosal |
| Upload Date | August 16 2024 04:58 PM |
| Views | 13 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
2097
390.0 IPS |
|
|
Image Classification (HP)
|
100% |
2497
464.4 IPS |
|
|
Image Classification (Q)
|
100% |
3530
656.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
2714
44.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2708
43.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
4368
71.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
4270
4.98 IPS |
|
|
Pose Estimation (HP)
|
100% |
3990
4.66 IPS |
|
|
Pose Estimation (Q)
|
84% |
9237
11.0 IPS |
|
|
Object Detection (SP)
|
98% |
2018
160.6 IPS |
|
|
Object Detection (HP)
|
98% |
1799
143.1 IPS |
|
|
Object Detection (Q)
|
87% |
2589
207.9 IPS |
|
|
Face Detection (SP)
|
100% |
3370
40.0 IPS |
|
|
Face Detection (HP)
|
100% |
3371
40.1 IPS |
|
|
Face Detection (Q)
|
95% |
5689
67.9 IPS |
|
|
Depth Estimation (SP)
|
98% |
3475
26.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
3488
27.0 IPS |
|
|
Depth Estimation (Q)
|
75% |
5109
41.4 IPS |
|
|
Style Transfer (SP)
|
89% |
8700
11.3 IPS |
|
|
Style Transfer (HP)
|
89% |
8692
11.3 IPS |
|
|
Style Transfer (Q)
|
98% |
16588
21.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1771
65.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1803
66.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4219
156.3 IPS |
|
|
Text Classification (SP)
|
100% |
763
1.02 KIPS |
|
|
Text Classification (HP)
|
99% |
758
1.01 KIPS |
|
|
Text Classification (Q)
|
88% |
653
880.2 IPS |
|
|
Machine Translation (SP)
|
100% |
1275
22.0 IPS |
|
|
Machine Translation (HP)
|
100% |
1505
25.9 IPS |
|
|
Machine Translation (Q)
|
50% |
796
28.3 IPS |
