iPhone 15 Pro Max
Geekbench AI Score
3883
Single Precision Score
6897
Half Precision Score
5636
Quantized Score
Geekbench AI 1.4.0 for iOS AArch64
Result Information
| Upload Date | August 31 2025 11:06 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.0 |
| 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 | 7.47 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1668
310.2 IPS |
|
|
Image Classification (HP)
|
100% |
2950
548.6 IPS |
|
|
Image Classification (Q)
|
96% |
2032
379.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
1585
25.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2332
37.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
3016
48.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
7835
9.14 IPS |
|
|
Pose Estimation (HP)
|
100% |
15948
18.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
13856
16.2 IPS |
|
|
Object Detection (SP)
|
100% |
1719
136.3 IPS |
|
|
Object Detection (HP)
|
97% |
3258
259.4 IPS |
|
|
Object Detection (Q)
|
94% |
2336
186.2 IPS |
|
|
Face Detection (SP)
|
100% |
3090
36.7 IPS |
|
|
Face Detection (HP)
|
100% |
6578
78.2 IPS |
|
|
Face Detection (Q)
|
100% |
3764
44.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
6811
52.5 IPS |
|
|
Depth Estimation (HP)
|
98% |
12686
98.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
8942
69.9 IPS |
|
|
Style Transfer (SP)
|
100% |
20899
26.9 IPS |
|
|
Style Transfer (HP)
|
100% |
33363
42.9 IPS |
|
|
Style Transfer (Q)
|
96% |
27777
35.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4753
175.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5715
211.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4321
159.5 IPS |
|
|
Text Classification (SP)
|
100% |
3342
4.46 KIPS |
|
|
Text Classification (HP)
|
99% |
6000
8.01 KIPS |
|
|
Text Classification (Q)
|
93% |
5727
7.69 KIPS |
|
|
Machine Translation (SP)
|
100% |
3137
54.0 IPS |
|
|
Machine Translation (HP)
|
98% |
7146
123.5 IPS |
|
|
Machine Translation (Q)
|
98% |
7050
121.8 IPS |
