iPhone 16 Pro Max
Geekbench AI Score
4370
Single Precision Score
32773
Half Precision Score
44291
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 19 2025 03:32 PM |
| Views | 1 |
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% |
2030
377.4 IPS |
|
|
Image Classification (HP)
|
100% |
14865
2.76 KIPS |
|
|
Image Classification (Q)
|
97% |
18638
3.48 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1798
29.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
18105
293.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
23665
383.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
8318
9.71 IPS |
|
|
Pose Estimation (HP)
|
100% |
139838
163.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
275170
322.5 IPS |
|
|
Object Detection (SP)
|
100% |
2220
176.1 IPS |
|
|
Object Detection (HP)
|
100% |
15609
1.24 KIPS |
|
|
Object Detection (Q)
|
91% |
21250
1.70 KIPS |
|
|
Face Detection (SP)
|
100% |
3456
41.1 IPS |
|
|
Face Detection (HP)
|
100% |
39366
467.7 IPS |
|
|
Face Detection (Q)
|
100% |
53131
631.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
7537
58.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
92816
715.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
151090
1.18 KIPS |
|
|
Style Transfer (SP)
|
100% |
19924
25.6 IPS |
|
|
Style Transfer (HP)
|
100% |
242398
311.6 IPS |
|
|
Style Transfer (Q)
|
96% |
294575
380.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4906
181.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50734
1.87 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
76910
2.84 KIPS |
|
|
Text Classification (SP)
|
100% |
3685
4.92 KIPS |
|
|
Text Classification (HP)
|
99% |
6111
8.16 KIPS |
|
|
Text Classification (Q)
|
93% |
6115
8.21 KIPS |
|
|
Machine Translation (SP)
|
100% |
4019
69.2 IPS |
|
|
Machine Translation (HP)
|
100% |
8862
152.7 IPS |
|
|
Machine Translation (Q)
|
98% |
10130
175.1 IPS |
