Samsung Galaxy S24+
Geekbench AI Score
2565
Single Precision Score
11205
Half Precision Score
21979
Quantized Score
Geekbench AI 1.1.0-Beta2 Corporate for Android AArch64
Result Information
| User | wudi890 |
| Upload Date | November 04 2024 06:35 PM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | ENN |
| Device | Samsung Exynos 2400 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S24+ |
| Model ID | samsung SM-S926B |
| Motherboard | s5e9945 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 10 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 1.96 GHz |
| Cluster 1 | 4 Cores @ 1.96 GHz |
| Cluster 2 | 3 Cores @ 2.59 GHz |
| Cluster 3 | 2 Cores @ 2.90 GHz |
| Cluster 4 | 1 Core @ 3.21 GHz |
| Memory Information | |
|---|---|
| Size | 10.95 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1155
214.8 IPS |
|
|
Image Classification (HP)
|
100% |
8669
1.61 KIPS |
|
|
Image Classification (Q)
|
100% |
26177
4.87 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2051
33.2 IPS |
|
|
Image Segmentation (HP)
|
78% |
6896
115.6 IPS |
|
|
Image Segmentation (Q)
|
95% |
27551
448.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
12331
14.4 IPS |
|
|
Pose Estimation (HP)
|
100% |
84602
98.7 IPS |
|
|
Pose Estimation (Q)
|
78% |
287144
347.2 IPS |
|
|
Object Detection (SP)
|
100% |
1282
101.7 IPS |
|
|
Object Detection (HP)
|
100% |
8090
641.7 IPS |
|
|
Object Detection (Q)
|
90% |
12637
1.01 KIPS |
|
|
Face Detection (SP)
|
100% |
3587
42.6 IPS |
|
|
Face Detection (HP)
|
100% |
21211
252.0 IPS |
|
|
Face Detection (Q)
|
96% |
51524
614.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
4420
34.0 IPS |
|
|
Depth Estimation (HP)
|
79% |
46020
365.5 IPS |
|
|
Depth Estimation (Q)
|
63% |
75047
695.0 IPS |
|
|
Style Transfer (SP)
|
100% |
13244
17.0 IPS |
|
|
Style Transfer (HP)
|
99% |
149479
192.2 IPS |
|
|
Style Transfer (Q)
|
98% |
244445
315.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3510
129.6 IPS |
|
|
Image Super-Resolution (HP)
|
81% |
15722
595.2 IPS |
|
|
Image Super-Resolution (Q)
|
83% |
29281
1.10 KIPS |
|
|
Text Classification (SP)
|
100% |
447
596.9 IPS |
|
|
Text Classification (HP)
|
100% |
448
597.9 IPS |
|
|
Text Classification (Q)
|
91% |
725
974.4 IPS |
|
|
Machine Translation (SP)
|
100% |
1002
17.3 IPS |
|
|
Machine Translation (HP)
|
99% |
742
12.8 IPS |
|
|
Machine Translation (Q)
|
59% |
501
11.5 IPS |
