iPhone 16 Pro Max
Geekbench AI Score
4474
Single Precision Score
33348
Half Precision Score
44705
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 18 2025 08:09 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.0 |
| 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 | 7.44 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2017
375.1 IPS |
|
|
Image Classification (HP)
|
100% |
14774
2.75 KIPS |
|
|
Image Classification (Q)
|
97% |
18515
3.46 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1790
29.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
18054
292.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
23558
381.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
9077
10.6 IPS |
|
|
Pose Estimation (HP)
|
100% |
151884
177.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
281159
329.5 IPS |
|
|
Object Detection (SP)
|
100% |
2189
173.7 IPS |
|
|
Object Detection (HP)
|
100% |
15735
1.25 KIPS |
|
|
Object Detection (Q)
|
91% |
21298
1.70 KIPS |
|
|
Face Detection (SP)
|
100% |
3580
42.5 IPS |
|
|
Face Detection (HP)
|
100% |
39562
470.1 IPS |
|
|
Face Detection (Q)
|
100% |
53020
630.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
8024
61.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
94372
727.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
154543
1.21 KIPS |
|
|
Style Transfer (SP)
|
100% |
20707
26.6 IPS |
|
|
Style Transfer (HP)
|
100% |
244273
314.0 IPS |
|
|
Style Transfer (Q)
|
96% |
295584
381.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5171
190.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
51770
1.91 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
79703
2.94 KIPS |
|
|
Text Classification (SP)
|
100% |
3704
4.94 KIPS |
|
|
Text Classification (HP)
|
99% |
6284
8.39 KIPS |
|
|
Text Classification (Q)
|
93% |
6240
8.37 KIPS |
|
|
Machine Translation (SP)
|
100% |
3936
67.8 IPS |
|
|
Machine Translation (HP)
|
100% |
8995
154.9 IPS |
|
|
Machine Translation (Q)
|
98% |
10135
175.1 IPS |
