iPhone 15
Geekbench AI Score
3451
Single Precision Score
22399
Half Precision Score
26502
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | Wierzbi |
| Upload Date | December 04 2024 08:30 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.1.1 |
| Model | iPhone 15 |
| Model ID | iPhone15,4 |
| Motherboard | D37AP |
| CPU Information | |
|---|---|
| Name | Apple A16 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.46 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 5.56 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1415
263.1 IPS |
|
|
Image Classification (HP)
|
100% |
10561
1.96 KIPS |
|
|
Image Classification (Q)
|
97% |
12830
2.39 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1473
23.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
14825
240.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
18638
302.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
6344
7.40 IPS |
|
|
Pose Estimation (HP)
|
100% |
93984
109.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
103415
121.2 IPS |
|
|
Object Detection (SP)
|
100% |
1564
124.0 IPS |
|
|
Object Detection (HP)
|
100% |
12955
1.03 KIPS |
|
|
Object Detection (Q)
|
91% |
15080
1.20 KIPS |
|
|
Face Detection (SP)
|
100% |
3183
37.8 IPS |
|
|
Face Detection (HP)
|
100% |
32649
387.9 IPS |
|
|
Face Detection (Q)
|
100% |
41319
491.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
5996
46.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
75821
584.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
97872
765.2 IPS |
|
|
Style Transfer (SP)
|
100% |
17607
22.6 IPS |
|
|
Style Transfer (HP)
|
100% |
176079
226.4 IPS |
|
|
Style Transfer (Q)
|
96% |
178739
230.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3926
145.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
31272
1.15 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
36570
1.35 KIPS |
|
|
Text Classification (SP)
|
100% |
2609
3.48 KIPS |
|
|
Text Classification (HP)
|
100% |
2191
2.92 KIPS |
|
|
Text Classification (Q)
|
93% |
2910
3.91 KIPS |
|
|
Machine Translation (SP)
|
100% |
3373
58.1 IPS |
|
|
Machine Translation (HP)
|
100% |
5584
96.2 IPS |
|
|
Machine Translation (Q)
|
98% |
5959
103.0 IPS |
