iPhone 15 Pro Max
Geekbench AI Score
3989
Single Precision Score
6826
Half Precision Score
5610
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | pavelve |
| Upload Date | September 24 2024 12:59 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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% |
1719
319.7 IPS |
|
|
Image Classification (HP)
|
100% |
2903
539.9 IPS |
|
|
Image Classification (Q)
|
96% |
2015
376.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1696
27.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2399
38.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
3079
49.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
8175
9.54 IPS |
|
|
Pose Estimation (HP)
|
100% |
16475
19.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
14445
16.9 IPS |
|
|
Object Detection (SP)
|
100% |
1792
142.1 IPS |
|
|
Object Detection (HP)
|
97% |
3361
267.5 IPS |
|
|
Object Detection (Q)
|
94% |
2331
185.8 IPS |
|
|
Face Detection (SP)
|
100% |
3187
37.9 IPS |
|
|
Face Detection (HP)
|
100% |
6712
79.7 IPS |
|
|
Face Detection (Q)
|
100% |
3843
45.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
7142
55.0 IPS |
|
|
Depth Estimation (HP)
|
98% |
13509
104.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
9305
72.7 IPS |
|
|
Style Transfer (SP)
|
100% |
21174
27.2 IPS |
|
|
Style Transfer (HP)
|
100% |
32621
41.9 IPS |
|
|
Style Transfer (Q)
|
96% |
27565
35.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4980
183.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5796
214.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4434
163.7 IPS |
|
|
Text Classification (SP)
|
100% |
3194
4.26 KIPS |
|
|
Text Classification (HP)
|
100% |
5501
7.34 KIPS |
|
|
Text Classification (Q)
|
93% |
5590
7.50 KIPS |
|
|
Machine Translation (SP)
|
100% |
3122
53.8 IPS |
|
|
Machine Translation (HP)
|
98% |
6042
104.4 IPS |
|
|
Machine Translation (Q)
|
98% |
6058
104.7 IPS |
