Samsung Galaxy S24 Ultra
Geekbench AI Score
1679
Single Precision Score
2618
Half Precision Score
2016
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 11 2025 07:40 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| 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% |
1010
187.9 IPS |
|
|
Image Classification (HP)
|
100% |
1467
272.8 IPS |
|
|
Image Classification (Q)
|
100% |
1333
247.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
2208
35.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
3810
61.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
2981
48.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
8435
9.84 IPS |
|
|
Pose Estimation (HP)
|
99% |
15106
17.7 IPS |
|
|
Pose Estimation (Q)
|
96% |
14886
17.4 IPS |
|
|
Object Detection (SP)
|
100% |
962
76.3 IPS |
|
|
Object Detection (HP)
|
99% |
1463
116.1 IPS |
|
|
Object Detection (Q)
|
87% |
1397
112.2 IPS |
|
|
Face Detection (SP)
|
100% |
3650
43.4 IPS |
|
|
Face Detection (HP)
|
100% |
5844
69.4 IPS |
|
|
Face Detection (Q)
|
97% |
4629
55.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
4242
32.7 IPS |
|
|
Depth Estimation (HP)
|
98% |
6455
49.9 IPS |
|
|
Depth Estimation (Q)
|
61% |
4969
48.9 IPS |
|
|
Style Transfer (SP)
|
100% |
10168
13.1 IPS |
|
|
Style Transfer (HP)
|
100% |
22495
28.9 IPS |
|
|
Style Transfer (Q)
|
98% |
21129
27.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2338
86.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3839
141.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3750
139.0 IPS |
|
|
Text Classification (SP)
|
35% |
38
368.4 IPS |
|
|
Text Classification (HP)
|
35% |
51
465.5 IPS |
|
|
Text Classification (Q)
|
33% |
38
458.0 IPS |
|
|
Machine Translation (SP)
|
100% |
705
12.1 IPS |
|
|
Machine Translation (HP)
|
97% |
739
12.8 IPS |
|
|
Machine Translation (Q)
|
43% |
194
11.0 IPS |
