iPhone 16 Pro Max
Geekbench AI Score
4594
Single Precision Score
33070
Half Precision Score
44606
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 10 2025 05:04 AM |
| Views | 2 |
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% |
1984
368.9 IPS |
|
|
Image Classification (HP)
|
100% |
13881
2.58 KIPS |
|
|
Image Classification (Q)
|
97% |
18145
3.39 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1750
28.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
18135
294.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
23534
381.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
9404
11.0 IPS |
|
|
Pose Estimation (HP)
|
100% |
151997
177.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
290308
340.3 IPS |
|
|
Object Detection (SP)
|
100% |
2353
186.6 IPS |
|
|
Object Detection (HP)
|
100% |
15571
1.24 KIPS |
|
|
Object Detection (Q)
|
91% |
21235
1.70 KIPS |
|
|
Face Detection (SP)
|
100% |
3626
43.1 IPS |
|
|
Face Detection (HP)
|
100% |
39201
465.8 IPS |
|
|
Face Detection (Q)
|
100% |
52840
627.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
8104
62.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
94126
725.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
150711
1.18 KIPS |
|
|
Style Transfer (SP)
|
100% |
22294
28.7 IPS |
|
|
Style Transfer (HP)
|
100% |
244936
314.9 IPS |
|
|
Style Transfer (Q)
|
96% |
294599
380.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5525
204.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
51971
1.92 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
79251
2.93 KIPS |
|
|
Text Classification (SP)
|
100% |
3691
4.93 KIPS |
|
|
Text Classification (HP)
|
99% |
6219
8.30 KIPS |
|
|
Text Classification (Q)
|
93% |
6236
8.37 KIPS |
|
|
Machine Translation (SP)
|
100% |
4088
70.4 IPS |
|
|
Machine Translation (HP)
|
100% |
8991
154.9 IPS |
|
|
Machine Translation (Q)
|
98% |
10219
176.6 IPS |
