iPhone 16 Pro Max
Geekbench AI Score
4270
Single Precision Score
32679
Half Precision Score
44289
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | October 22 2025 10:11 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.0.1 |
| Model | iPhone 16 Pro Max |
| Model ID | iPhone17,2 |
| Motherboard | D94AP |
| CPU Information | |
|---|---|
| Name | Apple A18 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 4.04 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.44 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1981
368.4 IPS |
|
|
Image Classification (HP)
|
100% |
14559
2.71 KIPS |
|
|
Image Classification (Q)
|
97% |
17734
3.31 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1758
28.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
18120
293.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
23595
382.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
8288
9.67 IPS |
|
|
Pose Estimation (HP)
|
100% |
135797
158.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
273625
320.7 IPS |
|
|
Object Detection (SP)
|
100% |
2180
172.9 IPS |
|
|
Object Detection (HP)
|
100% |
15678
1.24 KIPS |
|
|
Object Detection (Q)
|
91% |
21509
1.72 KIPS |
|
|
Face Detection (SP)
|
100% |
3387
40.2 IPS |
|
|
Face Detection (HP)
|
100% |
39541
469.8 IPS |
|
|
Face Detection (Q)
|
100% |
53617
637.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
7455
57.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
92541
713.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
148253
1.16 KIPS |
|
|
Style Transfer (SP)
|
100% |
19444
25.0 IPS |
|
|
Style Transfer (HP)
|
100% |
242717
312.0 IPS |
|
|
Style Transfer (Q)
|
96% |
294759
380.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4662
172.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50922
1.88 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
80570
2.98 KIPS |
|
|
Text Classification (SP)
|
100% |
3674
4.90 KIPS |
|
|
Text Classification (HP)
|
99% |
6100
8.14 KIPS |
|
|
Text Classification (Q)
|
93% |
6186
8.30 KIPS |
|
|
Machine Translation (SP)
|
100% |
3812
65.7 IPS |
|
|
Machine Translation (HP)
|
100% |
8964
154.4 IPS |
|
|
Machine Translation (Q)
|
98% |
10099
174.5 IPS |
