iPhone 15
Geekbench AI Score
3339
Single Precision Score
22885
Half Precision Score
26230
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | justintea |
| Upload Date | December 06 2024 03:23 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% |
1450
269.7 IPS |
|
|
Image Classification (HP)
|
100% |
10632
1.98 KIPS |
|
|
Image Classification (Q)
|
97% |
12356
2.31 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1527
24.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
13563
219.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
18772
304.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
5663
6.61 IPS |
|
|
Pose Estimation (HP)
|
100% |
93109
108.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
101802
119.3 IPS |
|
|
Object Detection (SP)
|
100% |
1447
114.8 IPS |
|
|
Object Detection (HP)
|
100% |
12938
1.03 KIPS |
|
|
Object Detection (Q)
|
91% |
15016
1.20 KIPS |
|
|
Face Detection (SP)
|
100% |
3049
36.2 IPS |
|
|
Face Detection (HP)
|
100% |
31500
374.3 IPS |
|
|
Face Detection (Q)
|
100% |
40155
477.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
5520
42.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
74757
576.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
94888
741.9 IPS |
|
|
Style Transfer (SP)
|
100% |
16606
21.3 IPS |
|
|
Style Transfer (HP)
|
100% |
173372
222.9 IPS |
|
|
Style Transfer (Q)
|
96% |
174307
224.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3758
138.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
31509
1.16 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
37409
1.38 KIPS |
|
|
Text Classification (SP)
|
100% |
2659
3.55 KIPS |
|
|
Text Classification (HP)
|
100% |
2391
3.19 KIPS |
|
|
Text Classification (Q)
|
93% |
2155
2.89 KIPS |
|
|
Machine Translation (SP)
|
100% |
3406
58.7 IPS |
|
|
Machine Translation (HP)
|
100% |
7375
127.0 IPS |
|
|
Machine Translation (Q)
|
98% |
8123
140.4 IPS |
