Samsung Galaxy S24 Ultra
Geekbench AI Score
555
Single Precision Score
14351
Half Precision Score
36179
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | Cho_Seung_Woo |
| Upload Date | September 30 2024 01:47 PM |
| Views | 2 |
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% |
343
63.9 IPS |
|
|
Image Classification (HP)
|
100% |
17382
3.23 KIPS |
|
|
Image Classification (Q)
|
97% |
40958
7.64 KIPS |
|
|
Image Segmentation (SP)
|
100% |
444
7.20 IPS |
|
|
Image Segmentation (HP)
|
100% |
9761
158.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
26673
433.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
611
0.71 IPS |
|
|
Pose Estimation (HP)
|
100% |
70595
82.4 IPS |
|
|
Pose Estimation (Q)
|
98% |
279814
327.5 IPS |
|
|
Object Detection (SP)
|
100% |
328
26.0 IPS |
|
|
Object Detection (HP)
|
100% |
13428
1.07 KIPS |
|
|
Object Detection (Q)
|
86% |
18099
1.46 KIPS |
|
|
Face Detection (SP)
|
100% |
814
9.68 IPS |
|
|
Face Detection (HP)
|
100% |
29081
345.5 IPS |
|
|
Face Detection (Q)
|
97% |
113230
1.35 KIPS |
|
|
Depth Estimation (SP)
|
100% |
715
5.51 IPS |
|
|
Depth Estimation (HP)
|
99% |
51785
399.0 IPS |
|
|
Depth Estimation (Q)
|
63% |
106804
1.00 KIPS |
|
|
Style Transfer (SP)
|
100% |
1130
1.45 IPS |
|
|
Style Transfer (HP)
|
24% |
3409
103.1 IPS |
|
|
Style Transfer (Q)
|
98% |
284507
366.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
382
14.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
37497
1.38 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
103045
3.82 KIPS |
|
|
Text Classification (SP)
|
100% |
471
629.0 IPS |
|
|
Text Classification (HP)
|
100% |
3123
4.17 KIPS |
|
|
Text Classification (Q)
|
93% |
6731
9.03 KIPS |
|
|
Machine Translation (SP)
|
100% |
769
13.3 IPS |
|
|
Machine Translation (HP)
|
100% |
3834
66.0 IPS |
|
|
Machine Translation (Q)
|
30% |
291
58.4 IPS |
