iPhone SE (3rd generation)
Geekbench AI Score
3214
Single Precision Score
5549
Half Precision Score
4479
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | MidniteMarv |
| Upload Date | February 11 2025 03:22 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.3 |
| Model | iPhone SE (3rd generation) |
| Model ID | iPhone14,6 |
| Motherboard | D49AP |
| CPU Information | |
|---|---|
| Name | Apple A15 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.23 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 3.80 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1360
253.0 IPS |
|
|
Image Classification (HP)
|
100% |
2356
438.1 IPS |
|
|
Image Classification (Q)
|
96% |
1633
305.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
1337
21.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2001
32.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
2480
40.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
6237
7.28 IPS |
|
|
Pose Estimation (HP)
|
100% |
13318
15.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
11330
13.3 IPS |
|
|
Object Detection (SP)
|
100% |
1407
111.6 IPS |
|
|
Object Detection (HP)
|
97% |
2648
210.8 IPS |
|
|
Object Detection (Q)
|
94% |
1875
149.4 IPS |
|
|
Face Detection (SP)
|
100% |
2700
32.1 IPS |
|
|
Face Detection (HP)
|
100% |
5533
65.7 IPS |
|
|
Face Detection (Q)
|
100% |
3079
36.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
5318
41.0 IPS |
|
|
Depth Estimation (HP)
|
98% |
10969
84.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
7399
57.8 IPS |
|
|
Style Transfer (SP)
|
100% |
16941
21.8 IPS |
|
|
Style Transfer (HP)
|
100% |
26237
33.7 IPS |
|
|
Style Transfer (Q)
|
96% |
21518
27.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3745
138.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4588
169.4 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3397
125.4 IPS |
|
|
Text Classification (SP)
|
100% |
2389
3.19 KIPS |
|
|
Text Classification (HP)
|
100% |
4075
5.44 KIPS |
|
|
Text Classification (Q)
|
93% |
4066
5.46 KIPS |
|
|
Machine Translation (SP)
|
100% |
3393
58.5 IPS |
|
|
Machine Translation (HP)
|
98% |
5594
96.7 IPS |
|
|
Machine Translation (Q)
|
98% |
5589
96.6 IPS |
