iPhone 15 Pro Max
Geekbench AI Score
3963
Single Precision Score
6903
Half Precision Score
5623
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | RobboR |
| Upload Date | January 06 2025 08:28 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.2 |
| 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 | 7.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1686
313.5 IPS |
|
|
Image Classification (HP)
|
100% |
2919
542.8 IPS |
|
|
Image Classification (Q)
|
96% |
2017
376.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1596
25.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
2415
39.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
3084
50.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
8278
9.66 IPS |
|
|
Pose Estimation (HP)
|
100% |
16813
19.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
14534
17.0 IPS |
|
|
Object Detection (SP)
|
100% |
1815
144.0 IPS |
|
|
Object Detection (HP)
|
97% |
3383
269.3 IPS |
|
|
Object Detection (Q)
|
94% |
2362
188.3 IPS |
|
|
Face Detection (SP)
|
100% |
3165
37.6 IPS |
|
|
Face Detection (HP)
|
100% |
6704
79.7 IPS |
|
|
Face Detection (Q)
|
100% |
3902
46.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
7061
54.4 IPS |
|
|
Depth Estimation (HP)
|
98% |
13522
104.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
9368
73.2 IPS |
|
|
Style Transfer (SP)
|
100% |
21260
27.3 IPS |
|
|
Style Transfer (HP)
|
100% |
32706
42.0 IPS |
|
|
Style Transfer (Q)
|
96% |
27626
35.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5024
185.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5882
217.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4434
163.7 IPS |
|
|
Text Classification (SP)
|
100% |
3211
4.29 KIPS |
|
|
Text Classification (HP)
|
100% |
5595
7.47 KIPS |
|
|
Text Classification (Q)
|
93% |
5502
7.38 KIPS |
|
|
Machine Translation (SP)
|
100% |
3084
53.1 IPS |
|
|
Machine Translation (HP)
|
98% |
6289
108.7 IPS |
|
|
Machine Translation (Q)
|
98% |
6011
103.9 IPS |
