Samsung Galaxy S24 Ultra
Geekbench AI Score
1506
Single Precision Score
2408
Half Precision Score
1769
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | September 18 2025 01:29 AM |
| Views | 2 |
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-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% |
1309
243.5 IPS |
|
|
Image Classification (HP)
|
100% |
1958
364.0 IPS |
|
|
Image Classification (Q)
|
100% |
1839
342.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
2813
45.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
4934
80.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
4017
65.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
10999
12.8 IPS |
|
|
Pose Estimation (HP)
|
99% |
18562
21.7 IPS |
|
|
Pose Estimation (Q)
|
96% |
9229
10.8 IPS |
|
|
Object Detection (SP)
|
100% |
866
68.7 IPS |
|
|
Object Detection (HP)
|
99% |
1274
101.0 IPS |
|
|
Object Detection (Q)
|
87% |
1303
104.6 IPS |
|
|
Face Detection (SP)
|
100% |
2621
31.1 IPS |
|
|
Face Detection (HP)
|
100% |
4542
54.0 IPS |
|
|
Face Detection (Q)
|
97% |
3749
44.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
2975
22.9 IPS |
|
|
Depth Estimation (HP)
|
98% |
4502
34.8 IPS |
|
|
Depth Estimation (Q)
|
61% |
3406
33.5 IPS |
|
|
Style Transfer (SP)
|
100% |
7520
9.67 IPS |
|
|
Style Transfer (HP)
|
100% |
16185
20.8 IPS |
|
|
Style Transfer (Q)
|
98% |
15890
20.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1665
61.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2661
98.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2545
94.3 IPS |
|
|
Text Classification (SP)
|
35% |
29
285.6 IPS |
|
|
Text Classification (HP)
|
35% |
43
390.2 IPS |
|
|
Text Classification (Q)
|
33% |
34
406.2 IPS |
|
|
Machine Translation (SP)
|
100% |
608
10.5 IPS |
|
|
Machine Translation (HP)
|
97% |
760
13.1 IPS |
|
|
Machine Translation (Q)
|
43% |
193
11.0 IPS |
