Samsung Galaxy S24 Ultra
Geekbench AI Score
1489
Single Precision Score
2445
Half Precision Score
1926
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | August 07 2025 05:38 AM |
| Views | 4 |
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% |
992
184.5 IPS |
|
|
Image Classification (HP)
|
100% |
1460
271.5 IPS |
|
|
Image Classification (Q)
|
100% |
1412
262.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
2192
35.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
3870
62.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
3131
50.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
8401
9.80 IPS |
|
|
Pose Estimation (HP)
|
99% |
15093
17.7 IPS |
|
|
Pose Estimation (Q)
|
96% |
14674
17.2 IPS |
|
|
Object Detection (SP)
|
100% |
605
48.0 IPS |
|
|
Object Detection (HP)
|
99% |
1049
83.2 IPS |
|
|
Object Detection (Q)
|
87% |
1016
81.6 IPS |
|
|
Face Detection (SP)
|
100% |
3274
38.9 IPS |
|
|
Face Detection (HP)
|
100% |
5903
70.1 IPS |
|
|
Face Detection (Q)
|
97% |
4800
57.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
3917
30.2 IPS |
|
|
Depth Estimation (HP)
|
98% |
5877
45.4 IPS |
|
|
Depth Estimation (Q)
|
61% |
4466
44.0 IPS |
|
|
Style Transfer (SP)
|
100% |
9015
11.6 IPS |
|
|
Style Transfer (HP)
|
100% |
19328
24.8 IPS |
|
|
Style Transfer (Q)
|
98% |
18980
24.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1983
73.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3509
129.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3430
127.1 IPS |
|
|
Text Classification (SP)
|
35% |
35
343.4 IPS |
|
|
Text Classification (HP)
|
35% |
48
437.0 IPS |
|
|
Text Classification (Q)
|
33% |
40
480.6 IPS |
|
|
Machine Translation (SP)
|
100% |
605
10.4 IPS |
|
|
Machine Translation (HP)
|
97% |
756
13.1 IPS |
|
|
Machine Translation (Q)
|
43% |
191
10.9 IPS |
