Samsung Galaxy S24 Ultra
Geekbench AI Score
1143
Single Precision Score
1637
Half Precision Score
1617
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | September 18 2024 08:55 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| 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 | 10.81 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
921
171.3 IPS |
|
|
Image Classification (HP)
|
100% |
747
138.9 IPS |
|
|
Image Classification (Q)
|
96% |
614
114.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1381
22.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
1271
20.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
1762
28.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
1100
1.28 IPS |
|
|
Pose Estimation (HP)
|
100% |
2672
3.12 IPS |
|
|
Pose Estimation (Q)
|
96% |
2667
3.13 IPS |
|
|
Object Detection (SP)
|
100% |
704
55.8 IPS |
|
|
Object Detection (HP)
|
100% |
1150
91.2 IPS |
|
|
Object Detection (Q)
|
87% |
1041
83.6 IPS |
|
|
Face Detection (SP)
|
100% |
2758
32.8 IPS |
|
|
Face Detection (HP)
|
100% |
3154
37.5 IPS |
|
|
Face Detection (Q)
|
97% |
2530
30.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
1870
14.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
3695
28.5 IPS |
|
|
Depth Estimation (Q)
|
63% |
3177
29.5 IPS |
|
|
Style Transfer (SP)
|
100% |
7259
9.33 IPS |
|
|
Style Transfer (HP)
|
100% |
11968
15.4 IPS |
|
|
Style Transfer (Q)
|
98% |
11639
15.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
537
19.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1715
63.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1697
62.9 IPS |
|
|
Text Classification (SP)
|
100% |
349
465.3 IPS |
|
|
Text Classification (HP)
|
100% |
350
467.4 IPS |
|
|
Text Classification (Q)
|
91% |
561
753.6 IPS |
|
|
Machine Translation (SP)
|
100% |
554
9.54 IPS |
|
|
Machine Translation (HP)
|
100% |
566
9.75 IPS |
|
|
Machine Translation (Q)
|
57% |
457
11.2 IPS |
