iPhone 15 Pro Max
Geekbench AI Score
3845
Single Precision Score
25355
Half Precision Score
35847
Quantized Score
Geekbench AI 1.4.0 for iOS AArch64
Result Information
| Upload Date | July 12 2025 04:57 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.5 |
| Model | iPhone 15 Pro Max |
| Model ID | iPhone16,2 |
| Motherboard | D84AP |
| CPU Information | |
|---|---|
| Name | Apple A17 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.78 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1676
311.7 IPS |
|
|
Image Classification (HP)
|
100% |
10845
2.02 KIPS |
|
|
Image Classification (Q)
|
97% |
15104
2.82 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1571
25.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
15461
250.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
21264
344.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
7407
8.64 IPS |
|
|
Pose Estimation (HP)
|
100% |
104543
122.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
203953
239.0 IPS |
|
|
Object Detection (SP)
|
100% |
1760
139.6 IPS |
|
|
Object Detection (HP)
|
100% |
13904
1.10 KIPS |
|
|
Object Detection (Q)
|
91% |
19351
1.55 KIPS |
|
|
Face Detection (SP)
|
100% |
3080
36.6 IPS |
|
|
Face Detection (HP)
|
100% |
36588
434.7 IPS |
|
|
Face Detection (Q)
|
100% |
52635
625.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
6736
51.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
78624
605.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
129437
1.01 KIPS |
|
|
Style Transfer (SP)
|
100% |
20446
26.3 IPS |
|
|
Style Transfer (HP)
|
100% |
203953
262.2 IPS |
|
|
Style Transfer (Q)
|
96% |
254366
328.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4696
173.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33844
1.25 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
62556
2.31 KIPS |
|
|
Text Classification (SP)
|
100% |
3256
4.35 KIPS |
|
|
Text Classification (HP)
|
100% |
3250
4.34 KIPS |
|
|
Text Classification (Q)
|
93% |
3390
4.55 KIPS |
|
|
Machine Translation (SP)
|
100% |
3175
54.7 IPS |
|
|
Machine Translation (HP)
|
100% |
6982
120.3 IPS |
|
|
Machine Translation (Q)
|
98% |
7522
130.0 IPS |
