Samsung Galaxy S24 Ultra
Geekbench AI Score
2452
Single Precision Score
2450
Half Precision Score
3747
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | January 06 2025 06:52 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
2325
432.4 IPS |
|
|
Image Classification (HP)
|
100% |
2317
430.8 IPS |
|
|
Image Classification (Q)
|
100% |
3400
632.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
2414
39.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
2408
39.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
4029
65.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
4286
5.00 IPS |
|
|
Pose Estimation (HP)
|
100% |
4256
4.97 IPS |
|
|
Pose Estimation (Q)
|
84% |
8379
9.94 IPS |
|
|
Object Detection (SP)
|
98% |
1790
142.5 IPS |
|
|
Object Detection (HP)
|
98% |
1609
128.0 IPS |
|
|
Object Detection (Q)
|
83% |
2495
201.5 IPS |
|
|
Face Detection (SP)
|
100% |
3249
38.6 IPS |
|
|
Face Detection (HP)
|
100% |
3413
40.6 IPS |
|
|
Face Detection (Q)
|
95% |
5625
67.2 IPS |
|
|
Depth Estimation (SP)
|
99% |
3387
26.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
3491
27.0 IPS |
|
|
Depth Estimation (Q)
|
64% |
5648
51.7 IPS |
|
|
Style Transfer (SP)
|
89% |
8600
11.2 IPS |
|
|
Style Transfer (HP)
|
89% |
8461
11.0 IPS |
|
|
Style Transfer (Q)
|
98% |
16638
21.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1712
63.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1843
68.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4151
153.8 IPS |
|
|
Text Classification (SP)
|
100% |
722
963.8 IPS |
|
|
Text Classification (HP)
|
99% |
725
967.4 IPS |
|
|
Text Classification (Q)
|
88% |
1173
1.58 KIPS |
|
|
Machine Translation (SP)
|
100% |
1561
26.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1516
26.1 IPS |
|
|
Machine Translation (Q)
|
50% |
741
26.3 IPS |
