iPhone 15
Geekbench AI Score
3352
Single Precision Score
22615
Half Precision Score
26634
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | justintea |
| Upload Date | January 30 2025 06:07 AM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.3 |
| 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% |
1449
269.4 IPS |
|
|
Image Classification (HP)
|
100% |
10430
1.94 KIPS |
|
|
Image Classification (Q)
|
97% |
12175
2.27 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1509
24.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
13641
221.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
18520
300.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
5878
6.86 IPS |
|
|
Pose Estimation (HP)
|
100% |
94502
110.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
104694
122.7 IPS |
|
|
Object Detection (SP)
|
100% |
1494
118.5 IPS |
|
|
Object Detection (HP)
|
100% |
12622
1.00 KIPS |
|
|
Object Detection (Q)
|
91% |
14964
1.20 KIPS |
|
|
Face Detection (SP)
|
100% |
3089
36.7 IPS |
|
|
Face Detection (HP)
|
100% |
31500
374.3 IPS |
|
|
Face Detection (Q)
|
100% |
41327
491.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
5501
42.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
74805
576.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
94956
742.4 IPS |
|
|
Style Transfer (SP)
|
100% |
16395
21.1 IPS |
|
|
Style Transfer (HP)
|
100% |
168124
216.1 IPS |
|
|
Style Transfer (Q)
|
96% |
172200
222.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3678
135.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
32315
1.19 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
39041
1.44 KIPS |
|
|
Text Classification (SP)
|
100% |
2681
3.58 KIPS |
|
|
Text Classification (HP)
|
100% |
2160
2.88 KIPS |
|
|
Text Classification (Q)
|
93% |
2322
3.12 KIPS |
|
|
Machine Translation (SP)
|
100% |
3398
58.5 IPS |
|
|
Machine Translation (HP)
|
100% |
7458
128.5 IPS |
|
|
Machine Translation (Q)
|
98% |
8301
143.5 IPS |
