iPhone 16 Pro Max
Geekbench AI Score
4627
Single Precision Score
32945
Half Precision Score
44287
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| User | M91 |
| Upload Date | November 30 2025 03:00 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.2 |
| 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% |
1980
368.3 IPS |
|
|
Image Classification (HP)
|
100% |
13613
2.53 KIPS |
|
|
Image Classification (Q)
|
97% |
17143
3.20 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1775
28.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
18103
293.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
23567
382.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
9570
11.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
151910
177.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
289366
339.2 IPS |
|
|
Object Detection (SP)
|
100% |
2358
187.0 IPS |
|
|
Object Detection (HP)
|
100% |
15633
1.24 KIPS |
|
|
Object Detection (Q)
|
91% |
21252
1.70 KIPS |
|
|
Face Detection (SP)
|
100% |
3669
43.6 IPS |
|
|
Face Detection (HP)
|
100% |
39569
470.2 IPS |
|
|
Face Detection (Q)
|
100% |
53266
632.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
8285
63.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
94635
729.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
152130
1.19 KIPS |
|
|
Style Transfer (SP)
|
100% |
23252
29.9 IPS |
|
|
Style Transfer (HP)
|
100% |
244287
314.0 IPS |
|
|
Style Transfer (Q)
|
96% |
294247
379.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5457
201.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
52369
1.93 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
80039
2.96 KIPS |
|
|
Text Classification (SP)
|
100% |
3592
4.79 KIPS |
|
|
Text Classification (HP)
|
99% |
5885
7.86 KIPS |
|
|
Text Classification (Q)
|
93% |
6048
8.12 KIPS |
|
|
Machine Translation (SP)
|
100% |
4100
70.6 IPS |
|
|
Machine Translation (HP)
|
100% |
9130
157.3 IPS |
|
|
Machine Translation (Q)
|
98% |
10122
174.9 IPS |
