iPhone 16 Pro Max
Geekbench AI Score
4493
Single Precision Score
33062
Half Precision Score
44532
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | October 25 2025 06:11 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% |
2028
377.1 IPS |
|
|
Image Classification (HP)
|
100% |
14693
2.73 KIPS |
|
|
Image Classification (Q)
|
97% |
18346
3.42 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1800
29.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
18160
294.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
23586
382.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
8603
10.0 IPS |
|
|
Pose Estimation (HP)
|
100% |
145739
170.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
279311
327.4 IPS |
|
|
Object Detection (SP)
|
100% |
2293
181.9 IPS |
|
|
Object Detection (HP)
|
100% |
15756
1.25 KIPS |
|
|
Object Detection (Q)
|
91% |
21128
1.69 KIPS |
|
|
Face Detection (SP)
|
100% |
3555
42.2 IPS |
|
|
Face Detection (HP)
|
100% |
39517
469.5 IPS |
|
|
Face Detection (Q)
|
100% |
53088
630.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
7907
60.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
93971
724.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
151374
1.18 KIPS |
|
|
Style Transfer (SP)
|
100% |
21227
27.3 IPS |
|
|
Style Transfer (HP)
|
100% |
243829
313.4 IPS |
|
|
Style Transfer (Q)
|
96% |
294863
380.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5255
194.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50317
1.86 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
79253
2.93 KIPS |
|
|
Text Classification (SP)
|
100% |
3681
4.91 KIPS |
|
|
Text Classification (HP)
|
99% |
6133
8.19 KIPS |
|
|
Text Classification (Q)
|
93% |
6158
8.26 KIPS |
|
|
Machine Translation (SP)
|
100% |
4040
69.6 IPS |
|
|
Machine Translation (HP)
|
100% |
9118
157.1 IPS |
|
|
Machine Translation (Q)
|
98% |
10388
179.5 IPS |
