iPhone 15
Geekbench AI Score
3289
Single Precision Score
22721
Half Precision Score
26797
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | justintea |
| Upload Date | December 12 2024 02:54 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.2 |
| 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% |
1423
264.6 IPS |
|
|
Image Classification (HP)
|
100% |
9939
1.85 KIPS |
|
|
Image Classification (Q)
|
97% |
12296
2.29 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1434
23.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
14311
232.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
18223
295.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
5697
6.65 IPS |
|
|
Pose Estimation (HP)
|
100% |
91586
106.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
101436
118.9 IPS |
|
|
Object Detection (SP)
|
100% |
1455
115.4 IPS |
|
|
Object Detection (HP)
|
100% |
12912
1.02 KIPS |
|
|
Object Detection (Q)
|
91% |
14975
1.20 KIPS |
|
|
Face Detection (SP)
|
100% |
2973
35.3 IPS |
|
|
Face Detection (HP)
|
100% |
31232
371.1 IPS |
|
|
Face Detection (Q)
|
100% |
40515
481.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
5453
42.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
74412
573.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
93481
730.9 IPS |
|
|
Style Transfer (SP)
|
100% |
16364
21.0 IPS |
|
|
Style Transfer (HP)
|
100% |
173157
222.6 IPS |
|
|
Style Transfer (Q)
|
96% |
176473
227.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3729
137.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
31212
1.15 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
38318
1.41 KIPS |
|
|
Text Classification (SP)
|
100% |
2630
3.51 KIPS |
|
|
Text Classification (HP)
|
100% |
2403
3.21 KIPS |
|
|
Text Classification (Q)
|
93% |
2785
3.74 KIPS |
|
|
Machine Translation (SP)
|
100% |
3374
58.1 IPS |
|
|
Machine Translation (HP)
|
100% |
7224
124.4 IPS |
|
|
Machine Translation (Q)
|
98% |
7867
136.0 IPS |
