iPhone 16 Pro Max
Geekbench AI Score
4471
Single Precision Score
33214
Half Precision Score
44388
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 22 2025 04:25 AM |
| Views | 3 |
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% |
1994
370.8 IPS |
|
|
Image Classification (HP)
|
100% |
14885
2.77 KIPS |
|
|
Image Classification (Q)
|
97% |
17807
3.32 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1762
28.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
18108
293.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
23690
384.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
8798
10.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
146092
170.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
288822
338.5 IPS |
|
|
Object Detection (SP)
|
100% |
2298
182.2 IPS |
|
|
Object Detection (HP)
|
100% |
15966
1.27 KIPS |
|
|
Object Detection (Q)
|
91% |
21062
1.68 KIPS |
|
|
Face Detection (SP)
|
100% |
3582
42.6 IPS |
|
|
Face Detection (HP)
|
100% |
39506
469.4 IPS |
|
|
Face Detection (Q)
|
100% |
53168
631.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
7844
60.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
93828
722.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
152245
1.19 KIPS |
|
|
Style Transfer (SP)
|
100% |
20848
26.8 IPS |
|
|
Style Transfer (HP)
|
100% |
243962
313.6 IPS |
|
|
Style Transfer (Q)
|
96% |
294552
380.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5138
189.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
51259
1.89 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
78458
2.90 KIPS |
|
|
Text Classification (SP)
|
100% |
3769
5.03 KIPS |
|
|
Text Classification (HP)
|
99% |
6167
8.23 KIPS |
|
|
Text Classification (Q)
|
93% |
6109
8.20 KIPS |
|
|
Machine Translation (SP)
|
100% |
3962
68.2 IPS |
|
|
Machine Translation (HP)
|
100% |
9091
156.6 IPS |
|
|
Machine Translation (Q)
|
98% |
10127
175.0 IPS |
