iPhone 16 Pro Max
Geekbench AI Score
4414
Single Precision Score
33067
Half Precision Score
44621
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | October 28 2025 06:12 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.0.1 |
| 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% |
2021
375.8 IPS |
|
|
Image Classification (HP)
|
100% |
14664
2.73 KIPS |
|
|
Image Classification (Q)
|
97% |
18488
3.45 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1715
27.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
18121
293.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
23751
385.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
8400
9.80 IPS |
|
|
Pose Estimation (HP)
|
100% |
144339
168.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
278469
326.4 IPS |
|
|
Object Detection (SP)
|
100% |
2285
181.2 IPS |
|
|
Object Detection (HP)
|
100% |
15530
1.23 KIPS |
|
|
Object Detection (Q)
|
91% |
21301
1.70 KIPS |
|
|
Face Detection (SP)
|
100% |
3528
41.9 IPS |
|
|
Face Detection (HP)
|
100% |
39441
468.6 IPS |
|
|
Face Detection (Q)
|
100% |
53047
630.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
7786
60.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
93454
720.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
151245
1.18 KIPS |
|
|
Style Transfer (SP)
|
100% |
20173
25.9 IPS |
|
|
Style Transfer (HP)
|
100% |
244196
313.9 IPS |
|
|
Style Transfer (Q)
|
96% |
294823
380.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5109
188.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50597
1.87 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
79071
2.92 KIPS |
|
|
Text Classification (SP)
|
100% |
3676
4.91 KIPS |
|
|
Text Classification (HP)
|
99% |
6304
8.41 KIPS |
|
|
Text Classification (Q)
|
93% |
6210
8.33 KIPS |
|
|
Machine Translation (SP)
|
100% |
4063
70.0 IPS |
|
|
Machine Translation (HP)
|
100% |
9140
157.4 IPS |
|
|
Machine Translation (Q)
|
98% |
10344
178.8 IPS |
