iPhone 16 Pro Max
Geekbench AI Score
4465
Single Precision Score
32886
Half Precision Score
44559
Quantized Score
Geekbench AI 1.6.1 for iOS AArch64
Result Information
| Upload Date | January 28 2026 04:35 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.2.1 |
| 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 | 7.44 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1959
364.3 IPS |
|
|
Image Classification (HP)
|
100% |
14602
2.72 KIPS |
|
|
Image Classification (Q)
|
97% |
17882
3.34 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1738
28.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
18155
294.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
23728
384.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
8337
9.73 IPS |
|
|
Pose Estimation (HP)
|
100% |
143217
167.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
288795
338.5 IPS |
|
|
Object Detection (SP)
|
100% |
2260
179.3 IPS |
|
|
Object Detection (HP)
|
100% |
15532
1.23 KIPS |
|
|
Object Detection (Q)
|
91% |
21818
1.74 KIPS |
|
|
Face Detection (SP)
|
100% |
3573
42.5 IPS |
|
|
Face Detection (HP)
|
100% |
39802
472.9 IPS |
|
|
Face Detection (Q)
|
100% |
53738
638.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
8131
62.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
94126
725.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
151552
1.18 KIPS |
|
|
Style Transfer (SP)
|
100% |
21788
28.0 IPS |
|
|
Style Transfer (HP)
|
100% |
245080
315.1 IPS |
|
|
Style Transfer (Q)
|
96% |
297067
383.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5135
189.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50727
1.87 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
78218
2.89 KIPS |
|
|
Text Classification (SP)
|
100% |
3710
4.95 KIPS |
|
|
Text Classification (HP)
|
99% |
6157
8.22 KIPS |
|
|
Text Classification (Q)
|
93% |
6079
8.16 KIPS |
|
|
Machine Translation (SP)
|
100% |
4079
70.3 IPS |
|
|
Machine Translation (HP)
|
100% |
8749
150.7 IPS |
|
|
Machine Translation (Q)
|
98% |
10034
173.4 IPS |
