iPhone 16 Pro Max
Geekbench AI Score
4387
Single Precision Score
33081
Half Precision Score
45964
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | blackowl |
| Upload Date | May 15 2025 09:01 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.5 |
| 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 | 7.45 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2072
385.4 IPS |
|
|
Image Classification (HP)
|
100% |
15587
2.90 KIPS |
|
|
Image Classification (Q)
|
97% |
20412
3.81 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1931
31.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
17948
291.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
24063
390.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
8014
9.35 IPS |
|
|
Pose Estimation (HP)
|
100% |
143448
167.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
290537
340.5 IPS |
|
|
Object Detection (SP)
|
100% |
2261
179.4 IPS |
|
|
Object Detection (HP)
|
100% |
16276
1.29 KIPS |
|
|
Object Detection (Q)
|
91% |
22564
1.80 KIPS |
|
|
Face Detection (SP)
|
100% |
3725
44.3 IPS |
|
|
Face Detection (HP)
|
100% |
41166
489.1 IPS |
|
|
Face Detection (Q)
|
100% |
58482
694.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
7815
60.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
94920
731.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
159471
1.25 KIPS |
|
|
Style Transfer (SP)
|
100% |
18615
23.9 IPS |
|
|
Style Transfer (HP)
|
100% |
245393
315.5 IPS |
|
|
Style Transfer (Q)
|
96% |
302801
390.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4938
182.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50907
1.88 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
83324
3.08 KIPS |
|
|
Text Classification (SP)
|
100% |
3374
4.50 KIPS |
|
|
Text Classification (HP)
|
100% |
4831
6.45 KIPS |
|
|
Text Classification (Q)
|
93% |
4957
6.65 KIPS |
|
|
Machine Translation (SP)
|
100% |
4039
69.6 IPS |
|
|
Machine Translation (HP)
|
100% |
10191
175.5 IPS |
|
|
Machine Translation (Q)
|
98% |
11208
193.7 IPS |
