Samsung Galaxy S24 Ultra
Geekbench AI Score
3086
Single Precision Score
3077
Half Precision Score
4942
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | September 16 2024 12:36 PM |
| Views | 1 |
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 | 10.83 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2163
402.2 IPS |
|
|
Image Classification (HP)
|
100% |
2261
420.6 IPS |
|
|
Image Classification (Q)
|
100% |
3214
597.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
2776
45.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2836
46.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
4399
71.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
5029
5.87 IPS |
|
|
Pose Estimation (HP)
|
100% |
4733
5.52 IPS |
|
|
Pose Estimation (Q)
|
84% |
10880
12.9 IPS |
|
|
Object Detection (SP)
|
98% |
2397
190.8 IPS |
|
|
Object Detection (HP)
|
98% |
2379
189.3 IPS |
|
|
Object Detection (Q)
|
83% |
3736
301.8 IPS |
|
|
Face Detection (SP)
|
100% |
4414
52.4 IPS |
|
|
Face Detection (HP)
|
100% |
4666
55.4 IPS |
|
|
Face Detection (Q)
|
95% |
8376
100.0 IPS |
|
|
Depth Estimation (SP)
|
99% |
4237
32.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
4183
32.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
8210
75.2 IPS |
|
|
Style Transfer (SP)
|
89% |
11180
14.5 IPS |
|
|
Style Transfer (HP)
|
89% |
11129
14.4 IPS |
|
|
Style Transfer (Q)
|
98% |
22221
28.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2298
84.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2307
85.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5809
215.3 IPS |
|
|
Text Classification (SP)
|
100% |
1113
1.49 KIPS |
|
|
Text Classification (HP)
|
99% |
1111
1.48 KIPS |
|
|
Text Classification (Q)
|
88% |
1705
2.30 KIPS |
|
|
Machine Translation (SP)
|
100% |
2024
34.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1895
32.6 IPS |
|
|
Machine Translation (Q)
|
50% |
1000
35.5 IPS |
