iPhone 16 Pro Max
Geekbench AI Score
4539
Single Precision Score
33321
Half Precision Score
44855
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 21 2025 04:25 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% |
2010
373.7 IPS |
|
|
Image Classification (HP)
|
100% |
14526
2.70 KIPS |
|
|
Image Classification (Q)
|
97% |
18159
3.39 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1758
28.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
18146
294.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
23611
382.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
8954
10.4 IPS |
|
|
Pose Estimation (HP)
|
100% |
151371
176.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
289407
339.2 IPS |
|
|
Object Detection (SP)
|
100% |
2289
181.6 IPS |
|
|
Object Detection (HP)
|
100% |
15613
1.24 KIPS |
|
|
Object Detection (Q)
|
91% |
21285
1.70 KIPS |
|
|
Face Detection (SP)
|
100% |
3579
42.5 IPS |
|
|
Face Detection (HP)
|
100% |
39510
469.5 IPS |
|
|
Face Detection (Q)
|
100% |
53829
639.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
8135
62.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
94407
727.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
152015
1.19 KIPS |
|
|
Style Transfer (SP)
|
100% |
21736
27.9 IPS |
|
|
Style Transfer (HP)
|
100% |
244775
314.7 IPS |
|
|
Style Transfer (Q)
|
96% |
295887
381.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5346
197.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
51625
1.91 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
82187
3.03 KIPS |
|
|
Text Classification (SP)
|
100% |
3711
4.95 KIPS |
|
|
Text Classification (HP)
|
99% |
6263
8.36 KIPS |
|
|
Text Classification (Q)
|
93% |
6127
8.22 KIPS |
|
|
Machine Translation (SP)
|
100% |
4090
70.4 IPS |
|
|
Machine Translation (HP)
|
100% |
9175
158.0 IPS |
|
|
Machine Translation (Q)
|
98% |
10239
177.0 IPS |
