iPhone 15 Pro Max
Geekbench AI Score
3781
Single Precision Score
6893
Half Precision Score
5666
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| User | Obrig |
| Upload Date | December 19 2025 09:05 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.2 |
| 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 | 7.47 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1556
289.3 IPS |
|
|
Image Classification (HP)
|
100% |
2972
552.7 IPS |
|
|
Image Classification (Q)
|
96% |
2036
380.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1532
24.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2322
37.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
3034
49.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
7719
9.01 IPS |
|
|
Pose Estimation (HP)
|
100% |
16818
19.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
14462
17.0 IPS |
|
|
Object Detection (SP)
|
100% |
1656
131.4 IPS |
|
|
Object Detection (HP)
|
97% |
3265
259.9 IPS |
|
|
Object Detection (Q)
|
94% |
2350
187.3 IPS |
|
|
Face Detection (SP)
|
100% |
3043
36.2 IPS |
|
|
Face Detection (HP)
|
100% |
6697
79.6 IPS |
|
|
Face Detection (Q)
|
100% |
3817
45.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
6721
51.8 IPS |
|
|
Depth Estimation (HP)
|
98% |
12687
98.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
8940
69.9 IPS |
|
|
Style Transfer (SP)
|
100% |
21097
27.1 IPS |
|
|
Style Transfer (HP)
|
100% |
33011
42.4 IPS |
|
|
Style Transfer (Q)
|
96% |
27600
35.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4601
169.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5620
207.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4328
159.8 IPS |
|
|
Text Classification (SP)
|
100% |
3184
4.25 KIPS |
|
|
Text Classification (HP)
|
99% |
5640
7.53 KIPS |
|
|
Text Classification (Q)
|
93% |
5536
7.43 KIPS |
|
|
Machine Translation (SP)
|
100% |
3107
53.5 IPS |
|
|
Machine Translation (HP)
|
98% |
7197
124.4 IPS |
|
|
Machine Translation (Q)
|
98% |
7204
124.5 IPS |
