iPhone 16 Pro Max
Geekbench AI Score
4632
Single Precision Score
33379
Half Precision Score
45948
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 13 2025 07:05 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.7 |
| 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 | 7.45 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2082
387.3 IPS |
|
|
Image Classification (HP)
|
100% |
15768
2.93 KIPS |
|
|
Image Classification (Q)
|
97% |
20836
3.89 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1917
31.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
18296
296.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
24152
391.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
9294
10.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
153141
178.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
292222
342.5 IPS |
|
|
Object Detection (SP)
|
100% |
2351
186.5 IPS |
|
|
Object Detection (HP)
|
100% |
16290
1.29 KIPS |
|
|
Object Detection (Q)
|
91% |
22709
1.81 KIPS |
|
|
Face Detection (SP)
|
100% |
3821
45.4 IPS |
|
|
Face Detection (HP)
|
100% |
41252
490.2 IPS |
|
|
Face Detection (Q)
|
100% |
58004
689.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
8330
64.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
95313
734.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
159054
1.24 KIPS |
|
|
Style Transfer (SP)
|
100% |
20465
26.3 IPS |
|
|
Style Transfer (HP)
|
100% |
245858
316.1 IPS |
|
|
Style Transfer (Q)
|
96% |
302320
390.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5556
205.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50696
1.87 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
84608
3.12 KIPS |
|
|
Text Classification (SP)
|
100% |
3395
4.53 KIPS |
|
|
Text Classification (HP)
|
100% |
4782
6.38 KIPS |
|
|
Text Classification (Q)
|
93% |
4529
6.08 KIPS |
|
|
Machine Translation (SP)
|
100% |
4244
73.1 IPS |
|
|
Machine Translation (HP)
|
100% |
10182
175.4 IPS |
|
|
Machine Translation (Q)
|
98% |
11754
203.1 IPS |
