iPhone 16 Pro Max
Geekbench AI Score
4624
Single Precision Score
33199
Half Precision Score
44686
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 13 2025 11:24 AM |
| 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% |
2024
376.5 IPS |
|
|
Image Classification (HP)
|
100% |
14178
2.64 KIPS |
|
|
Image Classification (Q)
|
97% |
17527
3.27 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1809
29.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
18167
294.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
23705
384.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
9390
11.0 IPS |
|
|
Pose Estimation (HP)
|
100% |
151796
177.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
291113
341.2 IPS |
|
|
Object Detection (SP)
|
100% |
2359
187.1 IPS |
|
|
Object Detection (HP)
|
100% |
15731
1.25 KIPS |
|
|
Object Detection (Q)
|
91% |
21236
1.70 KIPS |
|
|
Face Detection (SP)
|
100% |
3661
43.5 IPS |
|
|
Face Detection (HP)
|
100% |
39528
469.7 IPS |
|
|
Face Detection (Q)
|
100% |
53347
633.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
8282
63.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
94312
726.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
153666
1.20 KIPS |
|
|
Style Transfer (SP)
|
100% |
22435
28.8 IPS |
|
|
Style Transfer (HP)
|
100% |
244947
314.9 IPS |
|
|
Style Transfer (Q)
|
96% |
294067
379.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5392
199.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50679
1.87 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
81497
3.01 KIPS |
|
|
Text Classification (SP)
|
100% |
3690
4.93 KIPS |
|
|
Text Classification (HP)
|
99% |
6313
8.43 KIPS |
|
|
Text Classification (Q)
|
93% |
6078
8.16 KIPS |
|
|
Machine Translation (SP)
|
100% |
4079
70.3 IPS |
|
|
Machine Translation (HP)
|
100% |
9054
156.0 IPS |
|
|
Machine Translation (Q)
|
98% |
10353
178.9 IPS |
