Samsung Galaxy S24 Ultra
Geekbench AI Score
358
Single Precision Score
354
Half Precision Score
782
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Maximum_Game |
| Upload Date | February 16 2025 09:49 PM |
| Views | 4 |
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-S928U1 |
| 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% |
264
49.0 IPS |
|
|
Image Classification (HP)
|
100% |
247
45.9 IPS |
|
|
Image Classification (Q)
|
99% |
613
114.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
258
4.18 IPS |
|
|
Image Segmentation (HP)
|
100% |
261
4.22 IPS |
|
|
Image Segmentation (Q)
|
98% |
518
8.43 IPS |
|
|
Pose Estimation (SP)
|
100% |
368
0.43 IPS |
|
|
Pose Estimation (HP)
|
100% |
373
0.44 IPS |
|
|
Pose Estimation (Q)
|
98% |
1451
1.70 IPS |
|
|
Object Detection (SP)
|
100% |
194
15.4 IPS |
|
|
Object Detection (HP)
|
100% |
200
15.9 IPS |
|
|
Object Detection (Q)
|
87% |
580
46.6 IPS |
|
|
Face Detection (SP)
|
100% |
533
6.34 IPS |
|
|
Face Detection (HP)
|
100% |
538
6.39 IPS |
|
|
Face Detection (Q)
|
97% |
1165
13.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
456
3.51 IPS |
|
|
Depth Estimation (HP)
|
99% |
458
3.53 IPS |
|
|
Depth Estimation (Q)
|
64% |
984
8.93 IPS |
|
|
Style Transfer (SP)
|
100% |
738
0.95 IPS |
|
|
Style Transfer (HP)
|
100% |
681
0.88 IPS |
|
|
Style Transfer (Q)
|
98% |
1706
2.20 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
250
9.23 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
243
8.97 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
819
30.4 IPS |
|
|
Text Classification (SP)
|
100% |
300
399.9 IPS |
|
|
Text Classification (HP)
|
100% |
300
400.4 IPS |
|
|
Text Classification (Q)
|
91% |
511
687.5 IPS |
|
|
Machine Translation (SP)
|
100% |
534
9.21 IPS |
|
|
Machine Translation (HP)
|
100% |
535
9.21 IPS |
|
|
Machine Translation (Q)
|
57% |
396
9.68 IPS |
