Samsung Galaxy S24 Ultra
Geekbench AI Score
2486
Single Precision Score
2560
Half Precision Score
3747
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | August 21 2025 08:29 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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% |
2001
372.1 IPS |
|
|
Image Classification (HP)
|
100% |
2319
431.3 IPS |
|
|
Image Classification (Q)
|
100% |
3268
607.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
2443
39.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
2619
42.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
4297
69.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
4201
4.90 IPS |
|
|
Pose Estimation (HP)
|
100% |
4251
4.96 IPS |
|
|
Pose Estimation (Q)
|
84% |
8431
10.00 IPS |
|
|
Object Detection (SP)
|
98% |
1908
151.8 IPS |
|
|
Object Detection (HP)
|
98% |
1917
152.6 IPS |
|
|
Object Detection (Q)
|
83% |
2577
208.2 IPS |
|
|
Face Detection (SP)
|
100% |
3396
40.4 IPS |
|
|
Face Detection (HP)
|
100% |
3421
40.6 IPS |
|
|
Face Detection (Q)
|
95% |
5675
67.8 IPS |
|
|
Depth Estimation (SP)
|
99% |
3777
29.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
3763
29.1 IPS |
|
|
Depth Estimation (Q)
|
64% |
5063
46.4 IPS |
|
|
Style Transfer (SP)
|
89% |
8670
11.3 IPS |
|
|
Style Transfer (HP)
|
89% |
8701
11.3 IPS |
|
|
Style Transfer (Q)
|
98% |
16553
21.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1695
62.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1796
66.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4200
155.6 IPS |
|
|
Text Classification (SP)
|
100% |
727
970.1 IPS |
|
|
Text Classification (HP)
|
99% |
785
1.05 KIPS |
|
|
Text Classification (Q)
|
88% |
1232
1.66 KIPS |
|
|
Machine Translation (SP)
|
100% |
1683
29.0 IPS |
|
|
Machine Translation (HP)
|
100% |
1552
26.7 IPS |
|
|
Machine Translation (Q)
|
50% |
728
25.8 IPS |
