iPhone 16 Pro Max
Geekbench AI Score
4411
Single Precision Score
33309
Half Precision Score
45831
Quantized Score
Geekbench AI 1.4.0 for iOS AArch64
Result Information
| User | Nxb |
| Upload Date | August 28 2025 12:03 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.6.2 |
| 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% |
2014
374.5 IPS |
|
|
Image Classification (HP)
|
100% |
15848
2.95 KIPS |
|
|
Image Classification (Q)
|
97% |
21405
3.99 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1938
31.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
18324
297.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
24013
389.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
8548
9.97 IPS |
|
|
Pose Estimation (HP)
|
100% |
150799
176.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
291814
342.0 IPS |
|
|
Object Detection (SP)
|
100% |
2283
181.1 IPS |
|
|
Object Detection (HP)
|
100% |
16490
1.31 KIPS |
|
|
Object Detection (Q)
|
91% |
22704
1.81 KIPS |
|
|
Face Detection (SP)
|
100% |
3676
43.7 IPS |
|
|
Face Detection (HP)
|
100% |
40679
483.4 IPS |
|
|
Face Detection (Q)
|
100% |
57130
678.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
7740
59.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
94948
731.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
160717
1.26 KIPS |
|
|
Style Transfer (SP)
|
100% |
18255
23.5 IPS |
|
|
Style Transfer (HP)
|
100% |
245112
315.1 IPS |
|
|
Style Transfer (Q)
|
96% |
304438
392.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5150
190.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50910
1.88 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
83015
3.07 KIPS |
|
|
Text Classification (SP)
|
100% |
3382
4.51 KIPS |
|
|
Text Classification (HP)
|
100% |
4672
6.24 KIPS |
|
|
Text Classification (Q)
|
93% |
4591
6.16 KIPS |
|
|
Machine Translation (SP)
|
100% |
4055
69.8 IPS |
|
|
Machine Translation (HP)
|
100% |
10339
178.1 IPS |
|
|
Machine Translation (Q)
|
98% |
11271
194.8 IPS |
