iPhone 16 Pro Max
Geekbench AI Score
3741
Single Precision Score
28629
Half Precision Score
37511
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 11 2025 12:11 AM |
| Views | 4 |
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% |
1923
357.6 IPS |
|
|
Image Classification (HP)
|
100% |
14659
2.73 KIPS |
|
|
Image Classification (Q)
|
97% |
19262
3.59 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1518
24.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
13940
226.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
20426
331.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
5386
6.28 IPS |
|
|
Pose Estimation (HP)
|
100% |
127183
148.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
181138
212.3 IPS |
|
|
Object Detection (SP)
|
100% |
1969
156.2 IPS |
|
|
Object Detection (HP)
|
100% |
14113
1.12 KIPS |
|
|
Object Detection (Q)
|
91% |
17495
1.40 KIPS |
|
|
Face Detection (SP)
|
100% |
3171
37.7 IPS |
|
|
Face Detection (HP)
|
100% |
30121
357.9 IPS |
|
|
Face Detection (Q)
|
100% |
46726
555.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
6866
52.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
83835
645.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
118750
928.4 IPS |
|
|
Style Transfer (SP)
|
100% |
18006
23.1 IPS |
|
|
Style Transfer (HP)
|
100% |
201841
259.5 IPS |
|
|
Style Transfer (Q)
|
96% |
227467
293.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4747
175.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
40007
1.48 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
71823
2.65 KIPS |
|
|
Text Classification (SP)
|
100% |
3424
4.57 KIPS |
|
|
Text Classification (HP)
|
99% |
5859
7.82 KIPS |
|
|
Text Classification (Q)
|
93% |
5483
7.36 KIPS |
|
|
Machine Translation (SP)
|
100% |
2726
46.9 IPS |
|
|
Machine Translation (HP)
|
100% |
8441
145.4 IPS |
|
|
Machine Translation (Q)
|
98% |
8901
153.8 IPS |
