iPhone 16 Pro Max
Geekbench AI Score
4693
Single Precision Score
33396
Half Precision Score
46016
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 17 2025 04:25 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.7 |
| 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% |
2067
384.4 IPS |
|
|
Image Classification (HP)
|
100% |
15163
2.82 KIPS |
|
|
Image Classification (Q)
|
97% |
20189
3.77 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1983
32.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
18321
297.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
24185
392.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
9520
11.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
153566
179.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
292171
342.4 IPS |
|
|
Object Detection (SP)
|
100% |
2352
186.6 IPS |
|
|
Object Detection (HP)
|
100% |
16443
1.30 KIPS |
|
|
Object Detection (Q)
|
91% |
22504
1.80 KIPS |
|
|
Face Detection (SP)
|
100% |
3945
46.9 IPS |
|
|
Face Detection (HP)
|
100% |
41141
488.8 IPS |
|
|
Face Detection (Q)
|
100% |
56243
668.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
8373
64.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
95323
734.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
160083
1.25 KIPS |
|
|
Style Transfer (SP)
|
100% |
20783
26.7 IPS |
|
|
Style Transfer (HP)
|
100% |
245997
316.2 IPS |
|
|
Style Transfer (Q)
|
96% |
299550
386.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5645
208.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50344
1.86 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
85458
3.16 KIPS |
|
|
Text Classification (SP)
|
100% |
3429
4.58 KIPS |
|
|
Text Classification (HP)
|
100% |
4906
6.55 KIPS |
|
|
Text Classification (Q)
|
93% |
4941
6.63 KIPS |
|
|
Machine Translation (SP)
|
100% |
4251
73.2 IPS |
|
|
Machine Translation (HP)
|
100% |
10325
177.9 IPS |
|
|
Machine Translation (Q)
|
98% |
11645
201.2 IPS |
