iPhone 16 Pro Max
Geekbench AI Score
4669
Single Precision Score
33146
Half Precision Score
45728
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | October 22 2025 07:20 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.7.1 |
| 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 | 7.45 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2071
385.2 IPS |
|
|
Image Classification (HP)
|
100% |
15445
2.87 KIPS |
|
|
Image Classification (Q)
|
97% |
20321
3.79 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1982
32.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
18337
297.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
24234
392.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
9160
10.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
152514
178.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
292039
342.3 IPS |
|
|
Object Detection (SP)
|
100% |
2355
186.8 IPS |
|
|
Object Detection (HP)
|
100% |
16317
1.29 KIPS |
|
|
Object Detection (Q)
|
91% |
22779
1.82 KIPS |
|
|
Face Detection (SP)
|
100% |
3922
46.6 IPS |
|
|
Face Detection (HP)
|
100% |
39833
473.3 IPS |
|
|
Face Detection (Q)
|
100% |
56788
674.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
8368
64.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
95637
736.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
160239
1.25 KIPS |
|
|
Style Transfer (SP)
|
100% |
20872
26.8 IPS |
|
|
Style Transfer (HP)
|
100% |
246325
316.7 IPS |
|
|
Style Transfer (Q)
|
96% |
303667
391.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5643
208.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
51331
1.90 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
84717
3.13 KIPS |
|
|
Text Classification (SP)
|
100% |
3399
4.54 KIPS |
|
|
Text Classification (HP)
|
100% |
4577
6.11 KIPS |
|
|
Text Classification (Q)
|
93% |
4578
6.14 KIPS |
|
|
Machine Translation (SP)
|
100% |
4232
72.9 IPS |
|
|
Machine Translation (HP)
|
100% |
10303
177.5 IPS |
|
|
Machine Translation (Q)
|
98% |
11387
196.8 IPS |
