Samsung Galaxy S24 Ultra
Geekbench AI Score
474
Single Precision Score
16524
Half Precision Score
39882
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | Cho_Seung_Woo |
| Upload Date | September 14 2024 04:31 PM |
| Views | 32 |
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% |
300
55.9 IPS |
|
|
Image Classification (HP)
|
100% |
18400
3.42 KIPS |
|
|
Image Classification (Q)
|
97% |
43440
8.11 KIPS |
|
|
Image Segmentation (SP)
|
100% |
383
6.21 IPS |
|
|
Image Segmentation (HP)
|
100% |
11060
179.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
29516
479.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
495
0.58 IPS |
|
|
Pose Estimation (HP)
|
100% |
98516
115.0 IPS |
|
|
Pose Estimation (Q)
|
98% |
399337
467.4 IPS |
|
|
Object Detection (SP)
|
100% |
276
21.9 IPS |
|
|
Object Detection (HP)
|
100% |
16526
1.31 KIPS |
|
|
Object Detection (Q)
|
86% |
19580
1.57 KIPS |
|
|
Face Detection (SP)
|
100% |
701
8.33 IPS |
|
|
Face Detection (HP)
|
100% |
35956
427.2 IPS |
|
|
Face Detection (Q)
|
97% |
128526
1.53 KIPS |
|
|
Depth Estimation (SP)
|
100% |
602
4.64 IPS |
|
|
Depth Estimation (HP)
|
99% |
62475
481.3 IPS |
|
|
Depth Estimation (Q)
|
63% |
118235
1.11 KIPS |
|
|
Style Transfer (SP)
|
100% |
974
1.25 IPS |
|
|
Style Transfer (HP)
|
24% |
3866
116.9 IPS |
|
|
Style Transfer (Q)
|
98% |
306205
394.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
323
11.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
46060
1.70 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
111595
4.14 KIPS |
|
|
Text Classification (SP)
|
100% |
419
559.1 IPS |
|
|
Text Classification (HP)
|
100% |
3102
4.14 KIPS |
|
|
Text Classification (Q)
|
93% |
6744
9.05 KIPS |
|
|
Machine Translation (SP)
|
100% |
664
11.4 IPS |
|
|
Machine Translation (HP)
|
100% |
3692
63.6 IPS |
|
|
Machine Translation (Q)
|
30% |
290
58.2 IPS |
