iPhone 15 Pro Max
Geekbench AI Score
3954
Single Precision Score
7051
Half Precision Score
5698
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | Andji |
| Upload Date | April 11 2025 12:37 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.4 |
| 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% |
1622
301.6 IPS |
|
|
Image Classification (HP)
|
100% |
3004
558.7 IPS |
|
|
Image Classification (Q)
|
96% |
2046
382.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1639
26.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
2533
41.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
3060
49.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
8220
9.59 IPS |
|
|
Pose Estimation (HP)
|
100% |
16310
19.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
14110
16.5 IPS |
|
|
Object Detection (SP)
|
100% |
1784
141.5 IPS |
|
|
Object Detection (HP)
|
97% |
3311
263.6 IPS |
|
|
Object Detection (Q)
|
94% |
2368
188.7 IPS |
|
|
Face Detection (SP)
|
100% |
3139
37.3 IPS |
|
|
Face Detection (HP)
|
100% |
6721
79.9 IPS |
|
|
Face Detection (Q)
|
100% |
3815
45.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
7071
54.5 IPS |
|
|
Depth Estimation (HP)
|
98% |
12961
100.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
9046
70.7 IPS |
|
|
Style Transfer (SP)
|
100% |
21636
27.8 IPS |
|
|
Style Transfer (HP)
|
100% |
34414
44.2 IPS |
|
|
Style Transfer (Q)
|
96% |
28291
36.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4809
177.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6104
225.4 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4490
165.8 IPS |
|
|
Text Classification (SP)
|
100% |
3298
4.40 KIPS |
|
|
Text Classification (HP)
|
100% |
5766
7.70 KIPS |
|
|
Text Classification (Q)
|
93% |
5710
7.66 KIPS |
|
|
Machine Translation (SP)
|
100% |
3152
54.3 IPS |
|
|
Machine Translation (HP)
|
98% |
7013
121.2 IPS |
|
|
Machine Translation (Q)
|
98% |
6893
119.1 IPS |
