Samsung Galaxy S24 Ultra
Geekbench AI Score
1860
Single Precision Score
2896
Half Precision Score
2273
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | September 02 2025 08:46 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Samsung Galaxy S24 Ultra |
| Model ID | samsung SM-S928N |
| 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% |
911
169.4 IPS |
|
|
Image Classification (HP)
|
100% |
1285
239.0 IPS |
|
|
Image Classification (Q)
|
100% |
1485
276.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
2331
37.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
4078
66.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
3120
50.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
9406
11.0 IPS |
|
|
Pose Estimation (HP)
|
99% |
16670
19.5 IPS |
|
|
Pose Estimation (Q)
|
96% |
13526
15.8 IPS |
|
|
Object Detection (SP)
|
100% |
983
77.9 IPS |
|
|
Object Detection (HP)
|
99% |
1458
115.6 IPS |
|
|
Object Detection (Q)
|
87% |
1524
122.4 IPS |
|
|
Face Detection (SP)
|
100% |
4201
49.9 IPS |
|
|
Face Detection (HP)
|
100% |
6710
79.7 IPS |
|
|
Face Detection (Q)
|
97% |
5285
63.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
5000
38.5 IPS |
|
|
Depth Estimation (HP)
|
98% |
7510
58.0 IPS |
|
|
Depth Estimation (Q)
|
61% |
5755
56.7 IPS |
|
|
Style Transfer (SP)
|
100% |
12432
16.0 IPS |
|
|
Style Transfer (HP)
|
100% |
26209
33.7 IPS |
|
|
Style Transfer (Q)
|
98% |
25544
32.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2571
94.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4220
155.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4060
150.5 IPS |
|
|
Text Classification (SP)
|
35% |
44
425.8 IPS |
|
|
Text Classification (HP)
|
35% |
64
581.6 IPS |
|
|
Text Classification (Q)
|
33% |
48
574.1 IPS |
|
|
Machine Translation (SP)
|
100% |
859
14.8 IPS |
|
|
Machine Translation (HP)
|
97% |
916
15.8 IPS |
|
|
Machine Translation (Q)
|
43% |
255
14.5 IPS |
