iPhone 16 Pro Max
Geekbench AI Score
4588
Single Precision Score
33147
Half Precision Score
44576
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 21 2025 01:39 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% |
2036
378.6 IPS |
|
|
Image Classification (HP)
|
100% |
14326
2.66 KIPS |
|
|
Image Classification (Q)
|
97% |
18488
3.45 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1827
29.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
18134
294.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
23443
380.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
9118
10.6 IPS |
|
|
Pose Estimation (HP)
|
100% |
151321
176.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
288757
338.4 IPS |
|
|
Object Detection (SP)
|
100% |
2353
186.6 IPS |
|
|
Object Detection (HP)
|
100% |
15630
1.24 KIPS |
|
|
Object Detection (Q)
|
91% |
21494
1.72 KIPS |
|
|
Face Detection (SP)
|
100% |
3626
43.1 IPS |
|
|
Face Detection (HP)
|
100% |
39069
464.2 IPS |
|
|
Face Detection (Q)
|
100% |
52341
621.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
8076
62.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
93566
720.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
148139
1.16 KIPS |
|
|
Style Transfer (SP)
|
100% |
21394
27.5 IPS |
|
|
Style Transfer (HP)
|
100% |
243915
313.6 IPS |
|
|
Style Transfer (Q)
|
96% |
293812
379.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5455
201.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50961
1.88 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
79614
2.94 KIPS |
|
|
Text Classification (SP)
|
100% |
3699
4.94 KIPS |
|
|
Text Classification (HP)
|
99% |
6220
8.30 KIPS |
|
|
Text Classification (Q)
|
93% |
6145
8.25 KIPS |
|
|
Machine Translation (SP)
|
100% |
4097
70.6 IPS |
|
|
Machine Translation (HP)
|
100% |
9221
158.8 IPS |
|
|
Machine Translation (Q)
|
98% |
10332
178.6 IPS |
