iPhone 16 Pro Max
Geekbench AI Score
4511
Single Precision Score
33314
Half Precision Score
44691
Quantized Score
Geekbench AI 1.6.1 for iOS AArch64
Result Information
| User | M91 |
| Upload Date | January 03 2026 02:38 PM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.3 |
| 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% |
2001
372.0 IPS |
|
|
Image Classification (HP)
|
100% |
14850
2.76 KIPS |
|
|
Image Classification (Q)
|
97% |
18191
3.39 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1771
28.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
18121
293.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
23589
382.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
8630
10.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
149911
174.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
288371
338.0 IPS |
|
|
Object Detection (SP)
|
100% |
2320
184.1 IPS |
|
|
Object Detection (HP)
|
100% |
15474
1.23 KIPS |
|
|
Object Detection (Q)
|
91% |
21539
1.72 KIPS |
|
|
Face Detection (SP)
|
100% |
3594
42.7 IPS |
|
|
Face Detection (HP)
|
100% |
39959
474.8 IPS |
|
|
Face Detection (Q)
|
100% |
52873
628.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
8063
62.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
95370
734.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
157013
1.23 KIPS |
|
|
Style Transfer (SP)
|
100% |
21718
27.9 IPS |
|
|
Style Transfer (HP)
|
100% |
244988
314.9 IPS |
|
|
Style Transfer (Q)
|
96% |
294354
379.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5228
193.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
51484
1.90 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
78887
2.91 KIPS |
|
|
Text Classification (SP)
|
100% |
3695
4.93 KIPS |
|
|
Text Classification (HP)
|
99% |
6158
8.22 KIPS |
|
|
Text Classification (Q)
|
93% |
6107
8.20 KIPS |
|
|
Machine Translation (SP)
|
100% |
4047
69.7 IPS |
|
|
Machine Translation (HP)
|
100% |
9114
157.0 IPS |
|
|
Machine Translation (Q)
|
98% |
10130
175.1 IPS |
