Samsung Galaxy S24 Ultra
Geekbench AI Score
528
Single Precision Score
14111
Half Precision Score
36164
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | Cho_Seung_Woo |
| Upload Date | September 30 2024 01:51 PM |
| Views | 13 |
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% |
321
59.6 IPS |
|
|
Image Classification (HP)
|
100% |
14842
2.76 KIPS |
|
|
Image Classification (Q)
|
97% |
41074
7.67 KIPS |
|
|
Image Segmentation (SP)
|
100% |
412
6.69 IPS |
|
|
Image Segmentation (HP)
|
100% |
9810
159.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
26598
432.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
570
0.66 IPS |
|
|
Pose Estimation (HP)
|
100% |
69871
81.5 IPS |
|
|
Pose Estimation (Q)
|
98% |
279748
327.4 IPS |
|
|
Object Detection (SP)
|
100% |
315
25.0 IPS |
|
|
Object Detection (HP)
|
100% |
13428
1.07 KIPS |
|
|
Object Detection (Q)
|
86% |
18095
1.46 KIPS |
|
|
Face Detection (SP)
|
100% |
786
9.34 IPS |
|
|
Face Detection (HP)
|
100% |
29081
345.5 IPS |
|
|
Face Detection (Q)
|
97% |
112507
1.34 KIPS |
|
|
Depth Estimation (SP)
|
100% |
686
5.29 IPS |
|
|
Depth Estimation (HP)
|
99% |
51751
398.7 IPS |
|
|
Depth Estimation (Q)
|
63% |
106752
999.6 IPS |
|
|
Style Transfer (SP)
|
100% |
1081
1.39 IPS |
|
|
Style Transfer (HP)
|
24% |
3409
103.1 IPS |
|
|
Style Transfer (Q)
|
98% |
284422
366.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
367
13.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
37695
1.39 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
103051
3.82 KIPS |
|
|
Text Classification (SP)
|
100% |
455
606.8 IPS |
|
|
Text Classification (HP)
|
100% |
3123
4.17 KIPS |
|
|
Text Classification (Q)
|
93% |
6731
9.03 KIPS |
|
|
Machine Translation (SP)
|
100% |
737
12.7 IPS |
|
|
Machine Translation (HP)
|
100% |
3795
65.4 IPS |
|
|
Machine Translation (Q)
|
30% |
292
58.6 IPS |
