Samsung Galaxy S24 Ultra
Geekbench AI Score
531
Single Precision Score
14174
Half Precision Score
37677
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | Cho_Seung_Woo |
| Upload Date | September 30 2024 01:33 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% |
269
50.0 IPS |
|
|
Image Classification (HP)
|
100% |
15338
2.85 KIPS |
|
|
Image Classification (Q)
|
97% |
40761
7.61 KIPS |
|
|
Image Segmentation (SP)
|
100% |
373
6.05 IPS |
|
|
Image Segmentation (HP)
|
100% |
10180
165.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
29473
479.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
518
0.60 IPS |
|
|
Pose Estimation (HP)
|
100% |
71514
83.4 IPS |
|
|
Pose Estimation (Q)
|
98% |
283107
331.4 IPS |
|
|
Object Detection (SP)
|
100% |
335
26.5 IPS |
|
|
Object Detection (HP)
|
100% |
13407
1.06 KIPS |
|
|
Object Detection (Q)
|
86% |
19622
1.58 KIPS |
|
|
Face Detection (SP)
|
100% |
812
9.65 IPS |
|
|
Face Detection (HP)
|
100% |
31644
376.0 IPS |
|
|
Face Detection (Q)
|
97% |
128862
1.54 KIPS |
|
|
Depth Estimation (SP)
|
100% |
715
5.51 IPS |
|
|
Depth Estimation (HP)
|
99% |
47977
369.6 IPS |
|
|
Depth Estimation (Q)
|
63% |
117054
1.10 KIPS |
|
|
Style Transfer (SP)
|
100% |
1150
1.48 IPS |
|
|
Style Transfer (HP)
|
24% |
3407
103.1 IPS |
|
|
Style Transfer (Q)
|
98% |
284816
367.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
400
14.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
37622
1.39 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
103754
3.84 KIPS |
|
|
Text Classification (SP)
|
100% |
492
656.8 IPS |
|
|
Text Classification (HP)
|
100% |
3122
4.17 KIPS |
|
|
Text Classification (Q)
|
93% |
6706
9.00 KIPS |
|
|
Machine Translation (SP)
|
100% |
780
13.4 IPS |
|
|
Machine Translation (HP)
|
100% |
3600
62.0 IPS |
|
|
Machine Translation (Q)
|
30% |
289
58.1 IPS |
