Samsung Galaxy S24 Ultra
Geekbench AI Score
484
Single Precision Score
23592
Half Precision Score
58233
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | Cho_Seung_Woo |
| Upload Date | February 05 2026 06:14 AM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| 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% |
309
57.4 IPS |
|
|
Image Classification (HP)
|
100% |
18514
3.44 KIPS |
|
|
Image Classification (Q)
|
96% |
42103
7.86 KIPS |
|
|
Image Segmentation (SP)
|
100% |
385
6.24 IPS |
|
|
Image Segmentation (HP)
|
100% |
10794
175.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
39703
645.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
512
0.60 IPS |
|
|
Pose Estimation (HP)
|
100% |
101042
117.9 IPS |
|
|
Pose Estimation (Q)
|
98% |
398809
466.8 IPS |
|
|
Object Detection (SP)
|
100% |
287
22.7 IPS |
|
|
Object Detection (HP)
|
100% |
16723
1.33 KIPS |
|
|
Object Detection (Q)
|
86% |
26472
2.13 KIPS |
|
|
Face Detection (SP)
|
100% |
706
8.39 IPS |
|
|
Face Detection (HP)
|
100% |
33859
402.3 IPS |
|
|
Face Detection (Q)
|
97% |
123460
1.47 KIPS |
|
|
Depth Estimation (SP)
|
100% |
613
4.72 IPS |
|
|
Depth Estimation (HP)
|
99% |
62909
484.7 IPS |
|
|
Depth Estimation (Q)
|
63% |
144737
1.36 KIPS |
|
|
Style Transfer (SP)
|
100% |
993
1.28 IPS |
|
|
Style Transfer (HP)
|
100% |
80155
103.0 IPS |
|
|
Style Transfer (Q)
|
98% |
414340
534.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
324
12.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
45824
1.69 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
109026
4.04 KIPS |
|
|
Text Classification (SP)
|
100% |
431
575.4 IPS |
|
|
Text Classification (HP)
|
100% |
3788
5.06 KIPS |
|
|
Text Classification (Q)
|
93% |
9946
13.3 KIPS |
|
|
Machine Translation (SP)
|
100% |
681
11.7 IPS |
|
|
Machine Translation (HP)
|
100% |
5339
92.0 IPS |
|
|
Machine Translation (Q)
|
55% |
3165
82.9 IPS |
