iPhone 16 Pro Max
Geekbench AI Score
4640
Single Precision Score
35114
Half Precision Score
48076
Quantized Score
Geekbench AI 1.7.0 for iOS AArch64
Result Information
| User | Mladen |
| Upload Date | March 28 2026 09:57 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.4 |
| 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% |
1971
366.5 IPS |
|
|
Image Classification (HP)
|
100% |
14259
2.65 KIPS |
|
|
Image Classification (Q)
|
97% |
19062
3.56 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1823
29.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
18192
294.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
23790
385.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
7326
8.55 IPS |
|
|
Pose Estimation (HP)
|
100% |
152058
177.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
287454
336.9 IPS |
|
|
Object Detection (SP)
|
100% |
2364
187.5 IPS |
|
|
Object Detection (HP)
|
100% |
15498
1.23 KIPS |
|
|
Object Detection (Q)
|
89% |
21320
1.71 KIPS |
|
|
Face Detection (SP)
|
100% |
3843
45.7 IPS |
|
|
Face Detection (HP)
|
100% |
41125
488.7 IPS |
|
|
Face Detection (Q)
|
100% |
60796
722.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
7407
57.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
93847
723.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
152601
1.19 KIPS |
|
|
Style Transfer (SP)
|
100% |
19533
25.1 IPS |
|
|
Style Transfer (HP)
|
100% |
246389
316.7 IPS |
|
|
Style Transfer (Q)
|
96% |
294434
380.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4735
174.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50669
1.87 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
77349
2.86 KIPS |
|
|
Text Classification (SP)
|
100% |
6987
9.33 KIPS |
|
|
Text Classification (HP)
|
100% |
10745
14.3 KIPS |
|
|
Text Classification (Q)
|
93% |
10940
14.7 KIPS |
|
|
Machine Translation (SP)
|
100% |
4047
69.7 IPS |
|
|
Machine Translation (HP)
|
100% |
9006
155.1 IPS |
|
|
Machine Translation (Q)
|
98% |
10268
177.4 IPS |
