iPhone 16 Pro Max
Geekbench AI Score
4487
Single Precision Score
32915
Half Precision Score
44804
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 15 2025 06:17 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% |
2025
376.6 IPS |
|
|
Image Classification (HP)
|
100% |
13512
2.51 KIPS |
|
|
Image Classification (Q)
|
97% |
18856
3.52 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1830
29.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
18124
293.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
23749
385.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
9013
10.5 IPS |
|
|
Pose Estimation (HP)
|
100% |
148888
173.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
288736
338.4 IPS |
|
|
Object Detection (SP)
|
100% |
2326
184.5 IPS |
|
|
Object Detection (HP)
|
100% |
15499
1.23 KIPS |
|
|
Object Detection (Q)
|
91% |
21293
1.70 KIPS |
|
|
Face Detection (SP)
|
100% |
3629
43.1 IPS |
|
|
Face Detection (HP)
|
100% |
39651
471.1 IPS |
|
|
Face Detection (Q)
|
100% |
53631
637.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
8025
61.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
94073
724.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
152286
1.19 KIPS |
|
|
Style Transfer (SP)
|
100% |
21344
27.4 IPS |
|
|
Style Transfer (HP)
|
100% |
244783
314.7 IPS |
|
|
Style Transfer (Q)
|
96% |
296282
382.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5191
191.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
51232
1.89 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
78082
2.88 KIPS |
|
|
Text Classification (SP)
|
100% |
3748
5.00 KIPS |
|
|
Text Classification (HP)
|
99% |
6219
8.30 KIPS |
|
|
Text Classification (Q)
|
93% |
6158
8.27 KIPS |
|
|
Machine Translation (SP)
|
100% |
3521
60.6 IPS |
|
|
Machine Translation (HP)
|
100% |
9080
156.4 IPS |
|
|
Machine Translation (Q)
|
98% |
10176
175.9 IPS |
