iPhone 16 Pro Max
Geekbench AI Score
4637
Single Precision Score
33011
Half Precision Score
44428
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 11 2025 03:05 AM |
| Views | 3 |
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% |
2029
377.4 IPS |
|
|
Image Classification (HP)
|
100% |
13653
2.54 KIPS |
|
|
Image Classification (Q)
|
97% |
17511
3.27 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1829
29.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
18119
293.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
23644
383.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
9295
10.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
151813
177.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
290751
340.8 IPS |
|
|
Object Detection (SP)
|
100% |
2353
186.7 IPS |
|
|
Object Detection (HP)
|
100% |
15538
1.23 KIPS |
|
|
Object Detection (Q)
|
91% |
21302
1.70 KIPS |
|
|
Face Detection (SP)
|
100% |
3668
43.6 IPS |
|
|
Face Detection (HP)
|
100% |
39269
466.6 IPS |
|
|
Face Detection (Q)
|
100% |
52816
627.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
8257
63.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
95312
734.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
150295
1.18 KIPS |
|
|
Style Transfer (SP)
|
100% |
22951
29.5 IPS |
|
|
Style Transfer (HP)
|
100% |
244570
314.4 IPS |
|
|
Style Transfer (Q)
|
96% |
297123
383.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5276
194.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
51567
1.90 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
80420
2.97 KIPS |
|
|
Text Classification (SP)
|
100% |
3755
5.01 KIPS |
|
|
Text Classification (HP)
|
99% |
6116
8.16 KIPS |
|
|
Text Classification (Q)
|
93% |
6075
8.15 KIPS |
|
|
Machine Translation (SP)
|
100% |
4119
70.9 IPS |
|
|
Machine Translation (HP)
|
100% |
9123
157.1 IPS |
|
|
Machine Translation (Q)
|
98% |
10140
175.2 IPS |
