Samsung Galaxy S24 Ultra
Geekbench AI Score
345
Single Precision Score
349
Half Precision Score
768
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| User | tobbyng |
| Upload Date | September 04 2024 01:36 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-S9280 |
| 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% |
215
40.0 IPS |
|
|
Image Classification (HP)
|
100% |
216
40.2 IPS |
|
|
Image Classification (Q)
|
97% |
511
95.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
256
4.15 IPS |
|
|
Image Segmentation (HP)
|
100% |
258
4.19 IPS |
|
|
Image Segmentation (Q)
|
98% |
517
8.41 IPS |
|
|
Pose Estimation (SP)
|
100% |
357
0.42 IPS |
|
|
Pose Estimation (HP)
|
100% |
367
0.43 IPS |
|
|
Pose Estimation (Q)
|
98% |
1390
1.63 IPS |
|
|
Object Detection (SP)
|
100% |
205
16.2 IPS |
|
|
Object Detection (HP)
|
100% |
224
17.7 IPS |
|
|
Object Detection (Q)
|
89% |
579
46.4 IPS |
|
|
Face Detection (SP)
|
100% |
541
6.42 IPS |
|
|
Face Detection (HP)
|
100% |
545
6.48 IPS |
|
|
Face Detection (Q)
|
97% |
1230
14.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
441
3.40 IPS |
|
|
Depth Estimation (HP)
|
100% |
427
3.29 IPS |
|
|
Depth Estimation (Q)
|
73% |
1029
8.41 IPS |
|
|
Style Transfer (SP)
|
100% |
698
0.90 IPS |
|
|
Style Transfer (HP)
|
100% |
698
0.90 IPS |
|
|
Style Transfer (Q)
|
98% |
1662
2.14 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
233
8.59 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
232
8.55 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
786
29.1 IPS |
|
|
Text Classification (SP)
|
100% |
300
400.4 IPS |
|
|
Text Classification (HP)
|
100% |
317
423.7 IPS |
|
|
Text Classification (Q)
|
91% |
512
687.8 IPS |
|
|
Machine Translation (SP)
|
100% |
521
8.97 IPS |
|
|
Machine Translation (HP)
|
100% |
501
8.63 IPS |
|
|
Machine Translation (Q)
|
57% |
400
9.78 IPS |
