iPhone 16 Pro Max
Geekbench AI Score
4438
Single Precision Score
32791
Half Precision Score
45502
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | M91 |
| Upload Date | December 21 2024 12:43 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.3 |
| 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% |
1997
371.5 IPS |
|
|
Image Classification (HP)
|
100% |
15454
2.87 KIPS |
|
|
Image Classification (Q)
|
97% |
20480
3.82 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1926
31.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
18221
295.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
24041
389.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
8192
9.56 IPS |
|
|
Pose Estimation (HP)
|
100% |
149928
174.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
292413
342.7 IPS |
|
|
Object Detection (SP)
|
100% |
2109
167.3 IPS |
|
|
Object Detection (HP)
|
100% |
16312
1.29 KIPS |
|
|
Object Detection (Q)
|
91% |
22425
1.79 KIPS |
|
|
Face Detection (SP)
|
100% |
3524
41.9 IPS |
|
|
Face Detection (HP)
|
100% |
41252
490.2 IPS |
|
|
Face Detection (Q)
|
100% |
58096
690.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
7582
58.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
95860
738.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
160507
1.25 KIPS |
|
|
Style Transfer (SP)
|
100% |
23062
29.6 IPS |
|
|
Style Transfer (HP)
|
100% |
245453
315.5 IPS |
|
|
Style Transfer (Q)
|
96% |
300900
388.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5614
207.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
51142
1.89 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
83590
3.09 KIPS |
|
|
Text Classification (SP)
|
100% |
3415
4.56 KIPS |
|
|
Text Classification (HP)
|
100% |
4415
5.89 KIPS |
|
|
Text Classification (Q)
|
93% |
4404
5.91 KIPS |
|
|
Machine Translation (SP)
|
100% |
3776
65.0 IPS |
|
|
Machine Translation (HP)
|
100% |
9526
164.1 IPS |
|
|
Machine Translation (Q)
|
98% |
11411
197.2 IPS |
