iPhone 16 Pro Max
Geekbench AI Score
4556
Single Precision Score
32359
Half Precision Score
44973
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | April 13 2025 11:40 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.4 |
| 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 | 7.45 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2061
383.3 IPS |
|
|
Image Classification (HP)
|
100% |
15225
2.83 KIPS |
|
|
Image Classification (Q)
|
97% |
20554
3.84 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1955
31.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
18187
294.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
24124
391.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
9099
10.6 IPS |
|
|
Pose Estimation (HP)
|
100% |
151767
177.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
290837
340.9 IPS |
|
|
Object Detection (SP)
|
100% |
2303
182.7 IPS |
|
|
Object Detection (HP)
|
100% |
16149
1.28 KIPS |
|
|
Object Detection (Q)
|
91% |
22796
1.82 KIPS |
|
|
Face Detection (SP)
|
100% |
3796
45.1 IPS |
|
|
Face Detection (HP)
|
100% |
41188
489.4 IPS |
|
|
Face Detection (Q)
|
100% |
58149
690.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
8106
62.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
94780
730.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
163036
1.27 KIPS |
|
|
Style Transfer (SP)
|
100% |
19708
25.3 IPS |
|
|
Style Transfer (HP)
|
100% |
244804
314.7 IPS |
|
|
Style Transfer (Q)
|
96% |
303955
392.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5394
199.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50718
1.87 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
83455
3.08 KIPS |
|
|
Text Classification (SP)
|
100% |
3372
4.50 KIPS |
|
|
Text Classification (HP)
|
100% |
3858
5.15 KIPS |
|
|
Text Classification (Q)
|
93% |
4007
5.38 KIPS |
|
|
Machine Translation (SP)
|
100% |
4142
71.4 IPS |
|
|
Machine Translation (HP)
|
100% |
9920
170.9 IPS |
|
|
Machine Translation (Q)
|
98% |
10686
184.7 IPS |
