iPhone 16 Pro Max
Geekbench AI Score
4616
Single Precision Score
33018
Half Precision Score
44864
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 16 2025 07:19 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.0 |
| 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% |
2028
377.1 IPS |
|
|
Image Classification (HP)
|
100% |
14210
2.64 KIPS |
|
|
Image Classification (Q)
|
97% |
18922
3.53 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1810
29.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
18133
294.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
23603
382.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
9329
10.9 IPS |
|
|
Pose Estimation (HP)
|
100% |
151790
177.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
290509
340.5 IPS |
|
|
Object Detection (SP)
|
100% |
2358
187.0 IPS |
|
|
Object Detection (HP)
|
100% |
15608
1.24 KIPS |
|
|
Object Detection (Q)
|
91% |
21166
1.69 KIPS |
|
|
Face Detection (SP)
|
100% |
3654
43.4 IPS |
|
|
Face Detection (HP)
|
100% |
39183
465.6 IPS |
|
|
Face Detection (Q)
|
100% |
52925
628.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
8268
63.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
94117
725.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
150308
1.18 KIPS |
|
|
Style Transfer (SP)
|
100% |
22433
28.8 IPS |
|
|
Style Transfer (HP)
|
100% |
244841
314.7 IPS |
|
|
Style Transfer (Q)
|
96% |
295682
381.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5423
200.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50389
1.86 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
81039
2.99 KIPS |
|
|
Text Classification (SP)
|
100% |
3689
4.92 KIPS |
|
|
Text Classification (HP)
|
99% |
6141
8.20 KIPS |
|
|
Text Classification (Q)
|
93% |
6168
8.28 KIPS |
|
|
Machine Translation (SP)
|
100% |
4013
69.1 IPS |
|
|
Machine Translation (HP)
|
100% |
9029
155.5 IPS |
|
|
Machine Translation (Q)
|
98% |
10233
176.8 IPS |
