iPhone 15 Pro Max
Geekbench AI Score
3817
Single Precision Score
24384
Half Precision Score
33823
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | April 08 2025 03:51 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.4 |
| 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% |
1578
293.4 IPS |
|
|
Image Classification (HP)
|
100% |
10807
2.01 KIPS |
|
|
Image Classification (Q)
|
97% |
15339
2.86 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1590
25.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
16618
269.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
21270
344.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
7644
8.92 IPS |
|
|
Pose Estimation (HP)
|
100% |
105633
123.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
202856
237.8 IPS |
|
|
Object Detection (SP)
|
100% |
1758
139.4 IPS |
|
|
Object Detection (HP)
|
100% |
13988
1.11 KIPS |
|
|
Object Detection (Q)
|
91% |
18987
1.52 KIPS |
|
|
Face Detection (SP)
|
100% |
3104
36.9 IPS |
|
|
Face Detection (HP)
|
100% |
36417
432.7 IPS |
|
|
Face Detection (Q)
|
100% |
52500
623.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
6753
52.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
78004
601.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
125606
982.0 IPS |
|
|
Style Transfer (SP)
|
100% |
20139
25.9 IPS |
|
|
Style Transfer (HP)
|
100% |
206781
265.8 IPS |
|
|
Style Transfer (Q)
|
96% |
248438
320.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4570
168.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
35284
1.30 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
55734
2.06 KIPS |
|
|
Text Classification (SP)
|
100% |
3244
4.33 KIPS |
|
|
Text Classification (HP)
|
100% |
2097
2.80 KIPS |
|
|
Text Classification (Q)
|
93% |
2261
3.03 KIPS |
|
|
Machine Translation (SP)
|
100% |
3117
53.7 IPS |
|
|
Machine Translation (HP)
|
100% |
6444
111.0 IPS |
|
|
Machine Translation (Q)
|
98% |
7554
130.5 IPS |
