iPhone 16 Pro Max
Geekbench AI Score
4512
Single Precision Score
33152
Half Precision Score
44756
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | October 31 2025 06:53 AM |
| 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% |
1993
370.7 IPS |
|
|
Image Classification (HP)
|
100% |
14413
2.68 KIPS |
|
|
Image Classification (Q)
|
97% |
18781
3.50 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1753
28.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
18165
294.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
23439
380.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
8937
10.4 IPS |
|
|
Pose Estimation (HP)
|
100% |
151505
176.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
289430
339.2 IPS |
|
|
Object Detection (SP)
|
100% |
2305
182.8 IPS |
|
|
Object Detection (HP)
|
100% |
15673
1.24 KIPS |
|
|
Object Detection (Q)
|
91% |
21202
1.69 KIPS |
|
|
Face Detection (SP)
|
100% |
3526
41.9 IPS |
|
|
Face Detection (HP)
|
100% |
39495
469.3 IPS |
|
|
Face Detection (Q)
|
100% |
53352
633.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
8093
62.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
94205
725.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
154034
1.20 KIPS |
|
|
Style Transfer (SP)
|
100% |
21800
28.0 IPS |
|
|
Style Transfer (HP)
|
100% |
244975
314.9 IPS |
|
|
Style Transfer (Q)
|
96% |
294703
380.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5282
195.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
51173
1.89 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
78991
2.92 KIPS |
|
|
Text Classification (SP)
|
100% |
3690
4.92 KIPS |
|
|
Text Classification (HP)
|
99% |
6216
8.30 KIPS |
|
|
Text Classification (Q)
|
93% |
6179
8.29 KIPS |
|
|
Machine Translation (SP)
|
100% |
4015
69.2 IPS |
|
|
Machine Translation (HP)
|
100% |
8899
153.3 IPS |
|
|
Machine Translation (Q)
|
98% |
10100
174.5 IPS |
