Samsung Galaxy S24 Ultra
Geekbench AI Score
352
Single Precision Score
344
Half Precision Score
763
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | mohanadsinan |
| Upload Date | February 06 2025 10:57 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S24 Ultra |
| Model ID | samsung SM-S928B |
| 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% |
297
55.3 IPS |
|
|
Image Classification (HP)
|
100% |
294
54.6 IPS |
|
|
Image Classification (Q)
|
99% |
772
144.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
363
5.89 IPS |
|
|
Image Segmentation (HP)
|
100% |
369
5.99 IPS |
|
|
Image Segmentation (Q)
|
98% |
757
12.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
440
0.51 IPS |
|
|
Pose Estimation (HP)
|
100% |
329
0.38 IPS |
|
|
Pose Estimation (Q)
|
98% |
1256
1.47 IPS |
|
|
Object Detection (SP)
|
100% |
179
14.2 IPS |
|
|
Object Detection (HP)
|
100% |
179
14.2 IPS |
|
|
Object Detection (Q)
|
87% |
500
40.1 IPS |
|
|
Face Detection (SP)
|
100% |
463
5.50 IPS |
|
|
Face Detection (HP)
|
100% |
466
5.54 IPS |
|
|
Face Detection (Q)
|
97% |
1023
12.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
411
3.17 IPS |
|
|
Depth Estimation (HP)
|
99% |
412
3.17 IPS |
|
|
Depth Estimation (Q)
|
64% |
929
8.43 IPS |
|
|
Style Transfer (SP)
|
100% |
672
0.86 IPS |
|
|
Style Transfer (HP)
|
100% |
677
0.87 IPS |
|
|
Style Transfer (Q)
|
98% |
1636
2.11 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
216
7.98 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
228
8.43 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
710
26.3 IPS |
|
|
Text Classification (SP)
|
100% |
262
349.3 IPS |
|
|
Text Classification (HP)
|
100% |
260
347.7 IPS |
|
|
Text Classification (Q)
|
91% |
428
575.1 IPS |
|
|
Machine Translation (SP)
|
100% |
485
8.36 IPS |
|
|
Machine Translation (HP)
|
100% |
480
8.27 IPS |
|
|
Machine Translation (Q)
|
57% |
389
9.50 IPS |
