iPhone 16 Pro Max
Geekbench AI Score
4700
Single Precision Score
32957
Half Precision Score
45563
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | April 01 2025 01:51 PM |
| 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% |
2070
385.0 IPS |
|
|
Image Classification (HP)
|
100% |
15151
2.82 KIPS |
|
|
Image Classification (Q)
|
97% |
19006
3.55 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2002
32.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
18389
298.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
24138
391.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
9702
11.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
153520
179.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
292587
342.9 IPS |
|
|
Object Detection (SP)
|
100% |
2369
187.9 IPS |
|
|
Object Detection (HP)
|
100% |
16140
1.28 KIPS |
|
|
Object Detection (Q)
|
91% |
22442
1.79 KIPS |
|
|
Face Detection (SP)
|
100% |
3954
47.0 IPS |
|
|
Face Detection (HP)
|
100% |
41210
489.7 IPS |
|
|
Face Detection (Q)
|
100% |
57137
678.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
8356
64.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
96223
741.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
160074
1.25 KIPS |
|
|
Style Transfer (SP)
|
100% |
21059
27.1 IPS |
|
|
Style Transfer (HP)
|
100% |
246053
316.3 IPS |
|
|
Style Transfer (Q)
|
96% |
300790
388.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5630
207.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50756
1.87 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
83925
3.10 KIPS |
|
|
Text Classification (SP)
|
100% |
3382
4.51 KIPS |
|
|
Text Classification (HP)
|
100% |
4373
5.84 KIPS |
|
|
Text Classification (Q)
|
93% |
5034
6.76 KIPS |
|
|
Machine Translation (SP)
|
100% |
4169
71.8 IPS |
|
|
Machine Translation (HP)
|
100% |
10113
174.2 IPS |
|
|
Machine Translation (Q)
|
98% |
11014
190.3 IPS |
