Samsung Galaxy S24 Ultra
Geekbench AI Score
2526
Single Precision Score
2525
Half Precision Score
3537
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| User | Wilhelm |
| Upload Date | August 16 2024 01:13 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
2460
457.6 IPS |
|
|
Image Classification (HP)
|
100% |
2462
457.9 IPS |
|
|
Image Classification (Q)
|
100% |
3892
723.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
2623
42.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2683
43.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
4447
72.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
4304
5.02 IPS |
|
|
Pose Estimation (HP)
|
100% |
4236
4.94 IPS |
|
|
Pose Estimation (Q)
|
84% |
7949
9.43 IPS |
|
|
Object Detection (SP)
|
98% |
1740
138.5 IPS |
|
|
Object Detection (HP)
|
98% |
1747
139.0 IPS |
|
|
Object Detection (Q)
|
87% |
2488
199.8 IPS |
|
|
Face Detection (SP)
|
100% |
3404
40.4 IPS |
|
|
Face Detection (HP)
|
100% |
3401
40.4 IPS |
|
|
Face Detection (Q)
|
95% |
5810
69.4 IPS |
|
|
Depth Estimation (SP)
|
98% |
3884
30.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
3877
30.0 IPS |
|
|
Depth Estimation (Q)
|
75% |
6308
51.1 IPS |
|
|
Style Transfer (SP)
|
89% |
8499
11.0 IPS |
|
|
Style Transfer (HP)
|
89% |
8461
11.0 IPS |
|
|
Style Transfer (Q)
|
98% |
15773
20.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1692
62.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1738
64.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3938
145.9 IPS |
|
|
Text Classification (SP)
|
100% |
732
977.7 IPS |
|
|
Text Classification (HP)
|
99% |
725
967.5 IPS |
|
|
Text Classification (Q)
|
88% |
509
687.1 IPS |
|
|
Machine Translation (SP)
|
100% |
1576
27.2 IPS |
|
|
Machine Translation (HP)
|
100% |
1535
26.4 IPS |
|
|
Machine Translation (Q)
|
50% |
774
27.5 IPS |
