iPhone 16 Pro Max
Geekbench AI Score
4441
Single Precision Score
33070
Half Precision Score
44365
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | October 25 2025 05:07 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% |
1967
365.7 IPS |
|
|
Image Classification (HP)
|
100% |
14016
2.61 KIPS |
|
|
Image Classification (Q)
|
97% |
17544
3.27 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1720
27.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
18103
293.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
23598
382.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
8700
10.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
149562
174.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
288328
337.9 IPS |
|
|
Object Detection (SP)
|
100% |
2246
178.1 IPS |
|
|
Object Detection (HP)
|
100% |
15526
1.23 KIPS |
|
|
Object Detection (Q)
|
91% |
21073
1.68 KIPS |
|
|
Face Detection (SP)
|
100% |
3580
42.5 IPS |
|
|
Face Detection (HP)
|
100% |
39572
470.2 IPS |
|
|
Face Detection (Q)
|
100% |
53428
634.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
7994
61.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
94359
727.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
150295
1.18 KIPS |
|
|
Style Transfer (SP)
|
100% |
21218
27.3 IPS |
|
|
Style Transfer (HP)
|
100% |
244232
314.0 IPS |
|
|
Style Transfer (Q)
|
96% |
294359
379.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5076
187.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50553
1.87 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
79113
2.92 KIPS |
|
|
Text Classification (SP)
|
100% |
3681
4.91 KIPS |
|
|
Text Classification (HP)
|
99% |
6315
8.43 KIPS |
|
|
Text Classification (Q)
|
93% |
6102
8.19 KIPS |
|
|
Machine Translation (SP)
|
100% |
3983
68.6 IPS |
|
|
Machine Translation (HP)
|
100% |
9120
157.1 IPS |
|
|
Machine Translation (Q)
|
98% |
10292
177.9 IPS |
