Samsung Galaxy S24 Ultra
Geekbench AI Score
468
Single Precision Score
465
Half Precision Score
1010
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | PC2025 |
| Upload Date | January 13 2025 12:24 AM |
| 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-S928W |
| 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% |
317
59.0 IPS |
|
|
Image Classification (HP)
|
100% |
317
58.9 IPS |
|
|
Image Classification (Q)
|
99% |
824
153.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
406
6.58 IPS |
|
|
Image Segmentation (HP)
|
100% |
409
6.63 IPS |
|
|
Image Segmentation (Q)
|
98% |
820
13.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
559
0.65 IPS |
|
|
Pose Estimation (HP)
|
100% |
538
0.63 IPS |
|
|
Pose Estimation (Q)
|
98% |
1820
2.13 IPS |
|
|
Object Detection (SP)
|
100% |
287
22.8 IPS |
|
|
Object Detection (HP)
|
100% |
288
22.9 IPS |
|
|
Object Detection (Q)
|
87% |
745
59.7 IPS |
|
|
Face Detection (SP)
|
100% |
678
8.06 IPS |
|
|
Face Detection (HP)
|
100% |
670
7.96 IPS |
|
|
Face Detection (Q)
|
97% |
1493
17.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
576
4.44 IPS |
|
|
Depth Estimation (HP)
|
99% |
561
4.32 IPS |
|
|
Depth Estimation (Q)
|
64% |
1206
10.9 IPS |
|
|
Style Transfer (SP)
|
100% |
853
1.10 IPS |
|
|
Style Transfer (HP)
|
100% |
797
1.02 IPS |
|
|
Style Transfer (Q)
|
98% |
2002
2.58 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
299
11.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
314
11.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1040
38.5 IPS |
|
|
Text Classification (SP)
|
100% |
377
503.7 IPS |
|
|
Text Classification (HP)
|
100% |
378
504.8 IPS |
|
|
Text Classification (Q)
|
91% |
620
832.9 IPS |
|
|
Machine Translation (SP)
|
100% |
658
11.3 IPS |
|
|
Machine Translation (HP)
|
100% |
666
11.5 IPS |
|
|
Machine Translation (Q)
|
57% |
521
12.7 IPS |
