Samsung Galaxy S24 Ultra
Geekbench AI Score
2781
Single Precision Score
2829
Half Precision Score
4209
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | April 13 2025 01:51 PM |
| Views | 1 |
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-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% |
2134
396.9 IPS |
|
|
Image Classification (HP)
|
100% |
2427
451.3 IPS |
|
|
Image Classification (Q)
|
100% |
3224
599.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
2732
44.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2701
43.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
4232
68.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
4548
5.31 IPS |
|
|
Pose Estimation (HP)
|
100% |
4369
5.10 IPS |
|
|
Pose Estimation (Q)
|
84% |
10027
11.9 IPS |
|
|
Object Detection (SP)
|
98% |
2224
177.0 IPS |
|
|
Object Detection (HP)
|
98% |
2286
181.9 IPS |
|
|
Object Detection (Q)
|
83% |
3351
270.7 IPS |
|
|
Face Detection (SP)
|
100% |
4114
48.9 IPS |
|
|
Face Detection (HP)
|
100% |
4114
48.9 IPS |
|
|
Face Detection (Q)
|
95% |
7227
86.3 IPS |
|
|
Depth Estimation (SP)
|
99% |
4392
33.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
4298
33.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
7358
67.4 IPS |
|
|
Style Transfer (SP)
|
89% |
10063
13.1 IPS |
|
|
Style Transfer (HP)
|
89% |
9949
12.9 IPS |
|
|
Style Transfer (Q)
|
98% |
16610
21.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1707
63.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1947
71.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4512
167.2 IPS |
|
|
Text Classification (SP)
|
100% |
855
1.14 KIPS |
|
|
Text Classification (HP)
|
99% |
845
1.13 KIPS |
|
|
Text Classification (Q)
|
88% |
1289
1.74 KIPS |
|
|
Machine Translation (SP)
|
100% |
1774
30.6 IPS |
|
|
Machine Translation (HP)
|
100% |
1737
29.9 IPS |
|
|
Machine Translation (Q)
|
50% |
741
26.3 IPS |
