iPhone 16 Pro Max
Geekbench AI Score
4560
Single Precision Score
33097
Half Precision Score
44526
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 19 2025 08:09 AM |
| 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% |
2000
371.9 IPS |
|
|
Image Classification (HP)
|
100% |
14210
2.64 KIPS |
|
|
Image Classification (Q)
|
97% |
18635
3.48 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1756
28.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
18135
294.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
23764
385.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
8873
10.4 IPS |
|
|
Pose Estimation (HP)
|
100% |
151561
176.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
288542
338.2 IPS |
|
|
Object Detection (SP)
|
100% |
2326
184.5 IPS |
|
|
Object Detection (HP)
|
100% |
15547
1.23 KIPS |
|
|
Object Detection (Q)
|
91% |
20920
1.67 KIPS |
|
|
Face Detection (SP)
|
100% |
3635
43.2 IPS |
|
|
Face Detection (HP)
|
100% |
39521
469.6 IPS |
|
|
Face Detection (Q)
|
100% |
53072
630.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
8120
62.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
94138
725.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
152491
1.19 KIPS |
|
|
Style Transfer (SP)
|
100% |
22053
28.3 IPS |
|
|
Style Transfer (HP)
|
100% |
244062
313.7 IPS |
|
|
Style Transfer (Q)
|
96% |
293776
379.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5494
202.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
51577
1.90 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
78463
2.90 KIPS |
|
|
Text Classification (SP)
|
100% |
3692
4.93 KIPS |
|
|
Text Classification (HP)
|
99% |
6123
8.17 KIPS |
|
|
Text Classification (Q)
|
93% |
6123
8.22 KIPS |
|
|
Machine Translation (SP)
|
100% |
4068
70.1 IPS |
|
|
Machine Translation (HP)
|
100% |
9058
156.0 IPS |
|
|
Machine Translation (Q)
|
98% |
10033
173.4 IPS |
