Samsung Galaxy S24 Ultra
Geekbench AI Score
2420
Single Precision Score
2374
Half Precision Score
3569
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | October 13 2025 06:52 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | Samsung Galaxy S24 Ultra |
| Model ID | samsung SM-S928W |
| 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% |
2440
453.8 IPS |
|
|
Image Classification (HP)
|
100% |
2433
452.5 IPS |
|
|
Image Classification (Q)
|
100% |
3876
720.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
2607
42.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2588
42.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
3990
64.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
4206
4.91 IPS |
|
|
Pose Estimation (HP)
|
100% |
3462
4.04 IPS |
|
|
Pose Estimation (Q)
|
84% |
8043
9.54 IPS |
|
|
Object Detection (SP)
|
98% |
1742
138.6 IPS |
|
|
Object Detection (HP)
|
98% |
1768
140.7 IPS |
|
|
Object Detection (Q)
|
83% |
2197
177.5 IPS |
|
|
Face Detection (SP)
|
100% |
3372
40.1 IPS |
|
|
Face Detection (HP)
|
100% |
3368
40.0 IPS |
|
|
Face Detection (Q)
|
95% |
5380
64.2 IPS |
|
|
Depth Estimation (SP)
|
99% |
3488
27.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
3381
26.1 IPS |
|
|
Depth Estimation (Q)
|
64% |
5473
50.1 IPS |
|
|
Style Transfer (SP)
|
89% |
8407
10.9 IPS |
|
|
Style Transfer (HP)
|
89% |
8409
10.9 IPS |
|
|
Style Transfer (Q)
|
98% |
14893
19.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1418
52.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1640
60.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3777
140.0 IPS |
|
|
Text Classification (SP)
|
100% |
685
914.0 IPS |
|
|
Text Classification (HP)
|
99% |
684
913.6 IPS |
|
|
Text Classification (Q)
|
88% |
1113
1.50 KIPS |
|
|
Machine Translation (SP)
|
100% |
1540
26.5 IPS |
|
|
Machine Translation (HP)
|
100% |
1374
23.7 IPS |
|
|
Machine Translation (Q)
|
50% |
667
23.7 IPS |
