iPhone 16 Pro Max
Geekbench AI Score
4341
Single Precision Score
33282
Half Precision Score
45086
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 13 2025 10:41 AM |
| Views | 2 |
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% |
2016
374.9 IPS |
|
|
Image Classification (HP)
|
100% |
15021
2.79 KIPS |
|
|
Image Classification (Q)
|
97% |
19228
3.59 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1761
28.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
18135
294.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
23720
384.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
8248
9.62 IPS |
|
|
Pose Estimation (HP)
|
100% |
141737
165.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
284183
333.1 IPS |
|
|
Object Detection (SP)
|
100% |
2207
175.0 IPS |
|
|
Object Detection (HP)
|
100% |
15579
1.24 KIPS |
|
|
Object Detection (Q)
|
91% |
21259
1.70 KIPS |
|
|
Face Detection (SP)
|
100% |
3437
40.8 IPS |
|
|
Face Detection (HP)
|
100% |
40105
476.5 IPS |
|
|
Face Detection (Q)
|
100% |
54079
642.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
7538
58.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
92898
715.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
159527
1.25 KIPS |
|
|
Style Transfer (SP)
|
100% |
19721
25.4 IPS |
|
|
Style Transfer (HP)
|
100% |
242364
311.6 IPS |
|
|
Style Transfer (Q)
|
96% |
295572
381.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4859
179.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
52039
1.92 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
80842
2.99 KIPS |
|
|
Text Classification (SP)
|
100% |
3784
5.05 KIPS |
|
|
Text Classification (HP)
|
99% |
6525
8.71 KIPS |
|
|
Text Classification (Q)
|
93% |
6323
8.49 KIPS |
|
|
Machine Translation (SP)
|
100% |
3918
67.5 IPS |
|
|
Machine Translation (HP)
|
100% |
9043
155.8 IPS |
|
|
Machine Translation (Q)
|
98% |
9664
167.0 IPS |
