Samsung Galaxy S24 Ultra
Geekbench AI Score
2635
Single Precision Score
2635
Half Precision Score
4052
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | mersa |
| Upload Date | August 16 2025 09:06 AM |
| Views | 17 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
1495
278.1 IPS |
|
|
Image Classification (HP)
|
100% |
2414
448.9 IPS |
|
|
Image Classification (Q)
|
100% |
3200
595.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
2791
45.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
2776
45.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
4185
68.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
4439
5.18 IPS |
|
|
Pose Estimation (HP)
|
100% |
4246
4.95 IPS |
|
|
Pose Estimation (Q)
|
84% |
9860
11.7 IPS |
|
|
Object Detection (SP)
|
98% |
2122
168.9 IPS |
|
|
Object Detection (HP)
|
98% |
1981
157.6 IPS |
|
|
Object Detection (Q)
|
83% |
2681
216.6 IPS |
|
|
Face Detection (SP)
|
100% |
3802
45.2 IPS |
|
|
Face Detection (HP)
|
100% |
3792
45.1 IPS |
|
|
Face Detection (Q)
|
95% |
6408
76.5 IPS |
|
|
Depth Estimation (SP)
|
99% |
4039
31.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
3882
30.0 IPS |
|
|
Depth Estimation (Q)
|
64% |
6614
60.6 IPS |
|
|
Style Transfer (SP)
|
89% |
9965
12.9 IPS |
|
|
Style Transfer (HP)
|
89% |
9284
12.1 IPS |
|
|
Style Transfer (Q)
|
98% |
17901
23.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1918
70.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1979
73.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4409
163.4 IPS |
|
|
Text Classification (SP)
|
100% |
823
1.10 KIPS |
|
|
Text Classification (HP)
|
99% |
802
1.07 KIPS |
|
|
Text Classification (Q)
|
88% |
1352
1.82 KIPS |
|
|
Machine Translation (SP)
|
100% |
1701
29.3 IPS |
|
|
Machine Translation (HP)
|
100% |
1321
22.8 IPS |
|
|
Machine Translation (Q)
|
50% |
746
26.5 IPS |
