iPhone 15
Geekbench AI Score
3529
Single Precision Score
22728
Half Precision Score
26294
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | justintea |
| Upload Date | December 21 2024 03:09 AM |
| Views | 2 |
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% |
1426
265.1 IPS |
|
|
Image Classification (HP)
|
100% |
10120
1.88 KIPS |
|
|
Image Classification (Q)
|
97% |
12026
2.24 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1468
23.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
14228
230.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
18004
291.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
6731
7.85 IPS |
|
|
Pose Estimation (HP)
|
100% |
95780
111.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
101959
119.5 IPS |
|
|
Object Detection (SP)
|
100% |
1603
127.2 IPS |
|
|
Object Detection (HP)
|
100% |
12932
1.03 KIPS |
|
|
Object Detection (Q)
|
91% |
14640
1.17 KIPS |
|
|
Face Detection (SP)
|
100% |
3211
38.2 IPS |
|
|
Face Detection (HP)
|
100% |
31434
373.5 IPS |
|
|
Face Detection (Q)
|
100% |
40032
475.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
6095
47.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
74777
576.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
95591
747.4 IPS |
|
|
Style Transfer (SP)
|
100% |
18425
23.7 IPS |
|
|
Style Transfer (HP)
|
100% |
169834
218.3 IPS |
|
|
Style Transfer (Q)
|
96% |
172289
222.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4098
151.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
31551
1.17 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
36896
1.36 KIPS |
|
|
Text Classification (SP)
|
100% |
2631
3.51 KIPS |
|
|
Text Classification (HP)
|
100% |
2169
2.89 KIPS |
|
|
Text Classification (Q)
|
93% |
2447
3.28 KIPS |
|
|
Machine Translation (SP)
|
100% |
3417
58.9 IPS |
|
|
Machine Translation (HP)
|
100% |
7551
130.1 IPS |
|
|
Machine Translation (Q)
|
98% |
8212
141.9 IPS |
