iPhone 15 Pro Max
Geekbench AI Score
3510
Single Precision Score
5279
Half Precision Score
4394
Quantized Score
Geekbench AI 1.0.0 for iOS AArch64
Result Information
| User | sanjanah |
| Upload Date | August 16 2024 05:03 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| Model | iPhone 15 Pro Max |
| Model ID | iPhone16,2 |
| Motherboard | D84AP |
| CPU Information | |
|---|---|
| Name | Apple A17 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.78 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.44 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1660
308.8 IPS |
|
|
Image Classification (HP)
|
100% |
2165
402.6 IPS |
|
|
Image Classification (Q)
|
99% |
2203
410.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1369
22.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
1308
21.2 IPS |
|
|
Image Segmentation (Q)
|
100% |
1317
21.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
7086
8.27 IPS |
|
|
Pose Estimation (HP)
|
100% |
14970
17.5 IPS |
|
|
Pose Estimation (Q)
|
96% |
12793
15.0 IPS |
|
|
Object Detection (SP)
|
100% |
1652
131.0 IPS |
|
|
Object Detection (HP)
|
97% |
2481
197.5 IPS |
|
|
Object Detection (Q)
|
94% |
1921
153.1 IPS |
|
|
Face Detection (SP)
|
100% |
2756
32.7 IPS |
|
|
Face Detection (HP)
|
100% |
4758
56.5 IPS |
|
|
Face Detection (Q)
|
100% |
3020
35.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
5867
45.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
9362
72.3 IPS |
|
|
Depth Estimation (Q)
|
96% |
4767
36.9 IPS |
|
|
Style Transfer (SP)
|
100% |
18821
24.2 IPS |
|
|
Style Transfer (HP)
|
100% |
29144
37.5 IPS |
|
|
Style Transfer (Q)
|
100% |
29255
37.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4347
160.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5652
208.7 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
4197
155.5 IPS |
|
|
Text Classification (SP)
|
100% |
3008
4.01 KIPS |
|
|
Text Classification (HP)
|
100% |
4946
6.60 KIPS |
|
|
Text Classification (Q)
|
93% |
4856
6.52 KIPS |
|
|
Machine Translation (SP)
|
100% |
2683
46.2 IPS |
|
|
Machine Translation (HP)
|
98% |
4405
76.1 IPS |
|
|
Machine Translation (Q)
|
98% |
4393
75.9 IPS |
