iPhone 16 Pro Max
Geekbench AI Score
4257
Single Precision Score
32598
Half Precision Score
44646
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | October 15 2025 11:18 AM |
| Views | 4 |
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% |
1970
366.3 IPS |
|
|
Image Classification (HP)
|
100% |
14200
2.64 KIPS |
|
|
Image Classification (Q)
|
97% |
19210
3.58 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1683
27.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
18094
293.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
23635
383.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
7872
9.19 IPS |
|
|
Pose Estimation (HP)
|
100% |
139481
162.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
273691
320.8 IPS |
|
|
Object Detection (SP)
|
100% |
2217
175.9 IPS |
|
|
Object Detection (HP)
|
100% |
15643
1.24 KIPS |
|
|
Object Detection (Q)
|
91% |
21161
1.69 KIPS |
|
|
Face Detection (SP)
|
100% |
3397
40.4 IPS |
|
|
Face Detection (HP)
|
100% |
39598
470.5 IPS |
|
|
Face Detection (Q)
|
100% |
53711
638.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
7614
58.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
92529
712.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
153399
1.20 KIPS |
|
|
Style Transfer (SP)
|
100% |
18941
24.3 IPS |
|
|
Style Transfer (HP)
|
100% |
242807
312.1 IPS |
|
|
Style Transfer (Q)
|
96% |
294308
379.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4822
178.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
49716
1.84 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
80164
2.96 KIPS |
|
|
Text Classification (SP)
|
100% |
3706
4.95 KIPS |
|
|
Text Classification (HP)
|
99% |
6127
8.18 KIPS |
|
|
Text Classification (Q)
|
93% |
6159
8.27 KIPS |
|
|
Machine Translation (SP)
|
100% |
3862
66.5 IPS |
|
|
Machine Translation (HP)
|
100% |
8921
153.7 IPS |
|
|
Machine Translation (Q)
|
98% |
9996
172.7 IPS |
