iPhone 16 Pro Max
Geekbench AI Score
2927
Single Precision Score
3454
Half Precision Score
3309
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| User | M91 |
| Upload Date | October 16 2025 02:32 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.1 |
| 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% |
2847
529.4 IPS |
|
|
Image Classification (HP)
|
100% |
2550
474.2 IPS |
|
|
Image Classification (Q)
|
96% |
3079
574.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
4287
69.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
4910
79.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
4711
76.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
14881
17.4 IPS |
|
|
Pose Estimation (HP)
|
100% |
17929
20.9 IPS |
|
|
Pose Estimation (Q)
|
96% |
17379
20.4 IPS |
|
|
Object Detection (SP)
|
100% |
3089
245.0 IPS |
|
|
Object Detection (HP)
|
100% |
3333
264.4 IPS |
|
|
Object Detection (Q)
|
92% |
3167
252.8 IPS |
|
|
Face Detection (SP)
|
100% |
7409
88.0 IPS |
|
|
Face Detection (HP)
|
100% |
10608
126.0 IPS |
|
|
Face Detection (Q)
|
100% |
8602
102.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
13297
102.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
15772
121.5 IPS |
|
|
Depth Estimation (Q)
|
86% |
14166
110.6 IPS |
|
|
Style Transfer (SP)
|
100% |
31042
39.9 IPS |
|
|
Style Transfer (HP)
|
100% |
38867
50.0 IPS |
|
|
Style Transfer (Q)
|
96% |
39302
50.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
7317
270.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
8022
296.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
6819
251.8 IPS |
|
|
Text Classification (SP)
|
100% |
3680
4.91 KIPS |
|
|
Text Classification (HP)
|
99% |
6201
8.28 KIPS |
|
|
Text Classification (Q)
|
93% |
6049
8.12 KIPS |
|
|
Machine Translation (SP)
|
0% |
0
9.77 IPS |
|
|
Machine Translation (HP)
|
0% |
0
9.98 IPS |
|
|
Machine Translation (Q)
|
0% |
0
8.74 IPS |
