Samsung Galaxy S24 Ultra
Geekbench AI Score
475
Single Precision Score
467
Half Precision Score
1090
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| User | Cho_Seung_Woo |
| Upload Date | August 16 2024 05:21 AM |
| 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 | 10.81 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
300
55.8 IPS |
|
|
Image Classification (HP)
|
100% |
288
53.5 IPS |
|
|
Image Classification (Q)
|
97% |
759
141.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
373
6.04 IPS |
|
|
Image Segmentation (HP)
|
100% |
372
6.02 IPS |
|
|
Image Segmentation (Q)
|
98% |
772
12.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
493
0.58 IPS |
|
|
Pose Estimation (HP)
|
100% |
471
0.55 IPS |
|
|
Pose Estimation (Q)
|
98% |
1875
2.20 IPS |
|
|
Object Detection (SP)
|
100% |
281
22.3 IPS |
|
|
Object Detection (HP)
|
100% |
281
22.3 IPS |
|
|
Object Detection (Q)
|
89% |
803
64.3 IPS |
|
|
Face Detection (SP)
|
100% |
700
8.32 IPS |
|
|
Face Detection (HP)
|
100% |
674
8.01 IPS |
|
|
Face Detection (Q)
|
97% |
1663
19.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
604
4.66 IPS |
|
|
Depth Estimation (HP)
|
100% |
600
4.62 IPS |
|
|
Depth Estimation (Q)
|
73% |
1605
13.1 IPS |
|
|
Style Transfer (SP)
|
100% |
989
1.27 IPS |
|
|
Style Transfer (HP)
|
100% |
987
1.27 IPS |
|
|
Style Transfer (Q)
|
98% |
2400
3.09 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
315
11.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
316
11.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1082
40.1 IPS |
|
|
Text Classification (SP)
|
100% |
418
557.7 IPS |
|
|
Text Classification (HP)
|
100% |
424
566.4 IPS |
|
|
Text Classification (Q)
|
91% |
696
935.9 IPS |
|
|
Machine Translation (SP)
|
100% |
686
11.8 IPS |
|
|
Machine Translation (HP)
|
100% |
658
11.3 IPS |
|
|
Machine Translation (Q)
|
57% |
558
13.6 IPS |
