iPhone 16 Pro Max
Geekbench AI Score
4680
Single Precision Score
33060
Half Precision Score
44413
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 20 2025 06:33 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% |
2036
378.6 IPS |
|
|
Image Classification (HP)
|
100% |
13850
2.58 KIPS |
|
|
Image Classification (Q)
|
97% |
17533
3.27 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1826
29.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
18136
294.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
23707
384.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
9451
11.0 IPS |
|
|
Pose Estimation (HP)
|
100% |
152127
177.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
292187
342.5 IPS |
|
|
Object Detection (SP)
|
100% |
2363
187.4 IPS |
|
|
Object Detection (HP)
|
100% |
15534
1.23 KIPS |
|
|
Object Detection (Q)
|
91% |
21220
1.70 KIPS |
|
|
Face Detection (SP)
|
100% |
3660
43.5 IPS |
|
|
Face Detection (HP)
|
100% |
39389
468.0 IPS |
|
|
Face Detection (Q)
|
100% |
52901
628.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
8351
64.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
94269
726.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
147895
1.16 KIPS |
|
|
Style Transfer (SP)
|
100% |
23013
29.6 IPS |
|
|
Style Transfer (HP)
|
100% |
245239
315.3 IPS |
|
|
Style Transfer (Q)
|
96% |
295484
381.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5626
207.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
51633
1.91 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
79666
2.94 KIPS |
|
|
Text Classification (SP)
|
100% |
3697
4.93 KIPS |
|
|
Text Classification (HP)
|
99% |
6101
8.14 KIPS |
|
|
Text Classification (Q)
|
93% |
6075
8.15 KIPS |
|
|
Machine Translation (SP)
|
100% |
4156
71.6 IPS |
|
|
Machine Translation (HP)
|
100% |
9161
157.8 IPS |
|
|
Machine Translation (Q)
|
98% |
10358
179.0 IPS |
