Samsung Galaxy S24 Ultra
Geekbench AI Score
2304
Single Precision Score
2341
Half Precision Score
3458
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Spiike |
| Upload Date | April 13 2025 08:02 AM |
| Views | 8 |
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% |
1928
358.6 IPS |
|
|
Image Classification (HP)
|
100% |
2424
450.8 IPS |
|
|
Image Classification (Q)
|
100% |
3214
597.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
2513
40.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2602
42.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
4016
65.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
3995
4.66 IPS |
|
|
Pose Estimation (HP)
|
100% |
3297
3.85 IPS |
|
|
Pose Estimation (Q)
|
84% |
7529
8.93 IPS |
|
|
Object Detection (SP)
|
98% |
1625
129.4 IPS |
|
|
Object Detection (HP)
|
98% |
1652
131.5 IPS |
|
|
Object Detection (Q)
|
83% |
2121
171.3 IPS |
|
|
Face Detection (SP)
|
100% |
3249
38.6 IPS |
|
|
Face Detection (HP)
|
100% |
3277
38.9 IPS |
|
|
Face Detection (Q)
|
95% |
5119
61.1 IPS |
|
|
Depth Estimation (SP)
|
99% |
3278
25.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
3261
25.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
5271
48.3 IPS |
|
|
Style Transfer (SP)
|
89% |
8057
10.5 IPS |
|
|
Style Transfer (HP)
|
89% |
8095
10.5 IPS |
|
|
Style Transfer (Q)
|
98% |
15175
19.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1574
58.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1584
58.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3785
140.2 IPS |
|
|
Text Classification (SP)
|
100% |
662
883.0 IPS |
|
|
Text Classification (HP)
|
99% |
702
937.0 IPS |
|
|
Text Classification (Q)
|
88% |
1106
1.49 KIPS |
|
|
Machine Translation (SP)
|
100% |
1503
25.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1501
25.9 IPS |
|
|
Machine Translation (Q)
|
50% |
694
24.6 IPS |
