Samsung Galaxy S24 Ultra
Geekbench AI Score
496
Single Precision Score
14113
Half Precision Score
36056
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | Cho_Seung_Woo |
| Upload Date | September 30 2024 01:58 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S24 Ultra |
| Model ID | samsung SM-S928N |
| 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% |
312
58.0 IPS |
|
|
Image Classification (HP)
|
100% |
14906
2.77 KIPS |
|
|
Image Classification (Q)
|
97% |
41247
7.70 KIPS |
|
|
Image Segmentation (SP)
|
100% |
393
6.37 IPS |
|
|
Image Segmentation (HP)
|
100% |
9750
158.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
26537
431.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
529
0.62 IPS |
|
|
Pose Estimation (HP)
|
100% |
70563
82.3 IPS |
|
|
Pose Estimation (Q)
|
98% |
279610
327.3 IPS |
|
|
Object Detection (SP)
|
100% |
294
23.3 IPS |
|
|
Object Detection (HP)
|
100% |
13433
1.07 KIPS |
|
|
Object Detection (Q)
|
86% |
17966
1.44 KIPS |
|
|
Face Detection (SP)
|
100% |
725
8.62 IPS |
|
|
Face Detection (HP)
|
100% |
28951
344.0 IPS |
|
|
Face Detection (Q)
|
97% |
111377
1.33 KIPS |
|
|
Depth Estimation (SP)
|
100% |
633
4.88 IPS |
|
|
Depth Estimation (HP)
|
99% |
51600
397.6 IPS |
|
|
Depth Estimation (Q)
|
63% |
106749
999.6 IPS |
|
|
Style Transfer (SP)
|
100% |
1016
1.31 IPS |
|
|
Style Transfer (HP)
|
24% |
3406
103.1 IPS |
|
|
Style Transfer (Q)
|
98% |
283805
366.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
333
12.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
37689
1.39 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
103038
3.82 KIPS |
|
|
Text Classification (SP)
|
100% |
438
585.0 IPS |
|
|
Text Classification (HP)
|
100% |
3115
4.16 KIPS |
|
|
Text Classification (Q)
|
93% |
6722
9.02 KIPS |
|
|
Machine Translation (SP)
|
100% |
699
12.0 IPS |
|
|
Machine Translation (HP)
|
100% |
3812
65.7 IPS |
|
|
Machine Translation (Q)
|
30% |
289
58.1 IPS |
