Samsung Galaxy S24 Ultra
Geekbench AI Score
566
Single Precision Score
14384
Half Precision Score
36280
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | Cho_Seung_Woo |
| Upload Date | September 30 2024 12:32 PM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S24 Ultra |
| Model ID | samsung SM-S928N |
| 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% |
345
64.1 IPS |
|
|
Image Classification (HP)
|
100% |
18504
3.44 KIPS |
|
|
Image Classification (Q)
|
97% |
41074
7.67 KIPS |
|
|
Image Segmentation (SP)
|
100% |
445
7.21 IPS |
|
|
Image Segmentation (HP)
|
100% |
9761
158.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
26738
434.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
611
0.71 IPS |
|
|
Pose Estimation (HP)
|
100% |
69695
81.3 IPS |
|
|
Pose Estimation (Q)
|
98% |
280016
327.7 IPS |
|
|
Object Detection (SP)
|
100% |
340
26.9 IPS |
|
|
Object Detection (HP)
|
100% |
13456
1.07 KIPS |
|
|
Object Detection (Q)
|
86% |
18101
1.46 KIPS |
|
|
Face Detection (SP)
|
100% |
818
9.72 IPS |
|
|
Face Detection (HP)
|
100% |
29119
346.0 IPS |
|
|
Face Detection (Q)
|
97% |
112849
1.35 KIPS |
|
|
Depth Estimation (SP)
|
100% |
724
5.58 IPS |
|
|
Depth Estimation (HP)
|
99% |
51776
398.9 IPS |
|
|
Depth Estimation (Q)
|
63% |
106783
999.9 IPS |
|
|
Style Transfer (SP)
|
100% |
1158
1.49 IPS |
|
|
Style Transfer (HP)
|
24% |
3410
103.1 IPS |
|
|
Style Transfer (Q)
|
98% |
284663
367.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
402
14.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
37693
1.39 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
104484
3.87 KIPS |
|
|
Text Classification (SP)
|
100% |
494
659.5 IPS |
|
|
Text Classification (HP)
|
100% |
3105
4.14 KIPS |
|
|
Text Classification (Q)
|
93% |
6806
9.13 KIPS |
|
|
Machine Translation (SP)
|
100% |
790
13.6 IPS |
|
|
Machine Translation (HP)
|
100% |
3720
64.1 IPS |
|
|
Machine Translation (Q)
|
30% |
291
58.5 IPS |
