iPhone 16 Pro Max
Geekbench AI Score
4509
Single Precision Score
33078
Half Precision Score
44825
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | October 23 2025 10:29 PM |
| Views | 2 |
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% |
2032
378.0 IPS |
|
|
Image Classification (HP)
|
100% |
14834
2.76 KIPS |
|
|
Image Classification (Q)
|
97% |
18976
3.54 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1829
29.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
18116
293.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
23733
384.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
8744
10.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
149087
174.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
284648
333.6 IPS |
|
|
Object Detection (SP)
|
100% |
2310
183.2 IPS |
|
|
Object Detection (HP)
|
100% |
15647
1.24 KIPS |
|
|
Object Detection (Q)
|
91% |
21549
1.72 KIPS |
|
|
Face Detection (SP)
|
100% |
3576
42.5 IPS |
|
|
Face Detection (HP)
|
100% |
39971
474.9 IPS |
|
|
Face Detection (Q)
|
100% |
53423
634.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
7975
61.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
94208
725.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
151994
1.19 KIPS |
|
|
Style Transfer (SP)
|
100% |
20027
25.7 IPS |
|
|
Style Transfer (HP)
|
100% |
243991
313.7 IPS |
|
|
Style Transfer (Q)
|
96% |
296672
382.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5329
196.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50714
1.87 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
78003
2.88 KIPS |
|
|
Text Classification (SP)
|
100% |
3724
4.97 KIPS |
|
|
Text Classification (HP)
|
99% |
6320
8.44 KIPS |
|
|
Text Classification (Q)
|
93% |
6245
8.38 KIPS |
|
|
Machine Translation (SP)
|
100% |
4088
70.4 IPS |
|
|
Machine Translation (HP)
|
100% |
8495
146.3 IPS |
|
|
Machine Translation (Q)
|
98% |
10104
174.6 IPS |
