Samsung Galaxy S24 Ultra
Geekbench AI Score
387
Single Precision Score
382
Half Precision Score
858
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| User | leleletus |
| Upload Date | August 17 2024 03:54 PM |
| Views | 11 |
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 | 10.81 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
298
55.4 IPS |
|
|
Image Classification (HP)
|
100% |
296
55.0 IPS |
|
|
Image Classification (Q)
|
97% |
738
137.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
349
5.66 IPS |
|
|
Image Segmentation (HP)
|
100% |
356
5.77 IPS |
|
|
Image Segmentation (Q)
|
98% |
760
12.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
482
0.56 IPS |
|
|
Pose Estimation (HP)
|
100% |
397
0.46 IPS |
|
|
Pose Estimation (Q)
|
98% |
1385
1.62 IPS |
|
|
Object Detection (SP)
|
100% |
198
15.7 IPS |
|
|
Object Detection (HP)
|
100% |
203
16.1 IPS |
|
|
Object Detection (Q)
|
89% |
569
45.5 IPS |
|
|
Face Detection (SP)
|
100% |
502
5.96 IPS |
|
|
Face Detection (HP)
|
100% |
504
5.99 IPS |
|
|
Face Detection (Q)
|
97% |
1178
14.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
462
3.56 IPS |
|
|
Depth Estimation (HP)
|
100% |
463
3.56 IPS |
|
|
Depth Estimation (Q)
|
73% |
1145
9.36 IPS |
|
|
Style Transfer (SP)
|
100% |
739
0.95 IPS |
|
|
Style Transfer (HP)
|
100% |
740
0.95 IPS |
|
|
Style Transfer (Q)
|
98% |
1888
2.43 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
255
9.41 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
256
9.46 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
853
31.6 IPS |
|
|
Text Classification (SP)
|
100% |
318
423.9 IPS |
|
|
Text Classification (HP)
|
100% |
336
448.0 IPS |
|
|
Text Classification (Q)
|
91% |
543
729.3 IPS |
|
|
Machine Translation (SP)
|
100% |
547
9.43 IPS |
|
|
Machine Translation (HP)
|
100% |
529
9.11 IPS |
|
|
Machine Translation (Q)
|
57% |
418
10.2 IPS |
