iPhone 15
Geekbench AI Score
3434
Single Precision Score
5967
Half Precision Score
4797
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | justtea |
| Upload Date | November 20 2024 10:41 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| 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% |
1410
262.2 IPS |
|
|
Image Classification (HP)
|
100% |
2534
471.3 IPS |
|
|
Image Classification (Q)
|
96% |
1731
323.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1466
23.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2203
35.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
2695
43.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
6478
7.56 IPS |
|
|
Pose Estimation (HP)
|
100% |
14077
16.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
11933
14.0 IPS |
|
|
Object Detection (SP)
|
100% |
1543
122.4 IPS |
|
|
Object Detection (HP)
|
97% |
2901
230.9 IPS |
|
|
Object Detection (Q)
|
94% |
2044
163.0 IPS |
|
|
Face Detection (SP)
|
100% |
3172
37.7 IPS |
|
|
Face Detection (HP)
|
100% |
6057
72.0 IPS |
|
|
Face Detection (Q)
|
100% |
3370
40.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
5852
45.1 IPS |
|
|
Depth Estimation (HP)
|
98% |
12003
92.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
8014
62.6 IPS |
|
|
Style Transfer (SP)
|
100% |
17610
22.6 IPS |
|
|
Style Transfer (HP)
|
100% |
27337
35.1 IPS |
|
|
Style Transfer (Q)
|
96% |
22454
29.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3862
142.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4782
176.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3560
131.5 IPS |
|
|
Text Classification (SP)
|
100% |
2624
3.50 KIPS |
|
|
Text Classification (HP)
|
100% |
4612
6.16 KIPS |
|
|
Text Classification (Q)
|
93% |
4594
6.17 KIPS |
|
|
Machine Translation (SP)
|
100% |
3336
57.5 IPS |
|
|
Machine Translation (HP)
|
98% |
5728
99.0 IPS |
|
|
Machine Translation (Q)
|
98% |
5726
99.0 IPS |
