iPhone 15 Pro Max
Geekbench AI Score
3967
Single Precision Score
24850
Half Precision Score
34233
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | January 06 2025 11:23 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.2.1 |
| 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% |
1706
317.3 IPS |
|
|
Image Classification (HP)
|
100% |
10751
2.00 KIPS |
|
|
Image Classification (Q)
|
97% |
15120
2.82 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1607
26.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
15715
254.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
20926
339.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
8100
9.45 IPS |
|
|
Pose Estimation (HP)
|
100% |
106795
124.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
204464
239.6 IPS |
|
|
Object Detection (SP)
|
100% |
1811
143.6 IPS |
|
|
Object Detection (HP)
|
100% |
13694
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
19112
1.53 KIPS |
|
|
Face Detection (SP)
|
100% |
3178
37.8 IPS |
|
|
Face Detection (HP)
|
100% |
33746
401.0 IPS |
|
|
Face Detection (Q)
|
100% |
50346
598.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
7097
54.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
77962
600.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
129425
1.01 KIPS |
|
|
Style Transfer (SP)
|
100% |
21320
27.4 IPS |
|
|
Style Transfer (HP)
|
100% |
201408
258.9 IPS |
|
|
Style Transfer (Q)
|
96% |
246189
317.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5023
185.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33931
1.25 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
56818
2.10 KIPS |
|
|
Text Classification (SP)
|
100% |
3211
4.29 KIPS |
|
|
Text Classification (HP)
|
100% |
3256
4.35 KIPS |
|
|
Text Classification (Q)
|
93% |
2563
3.44 KIPS |
|
|
Machine Translation (SP)
|
100% |
3102
53.4 IPS |
|
|
Machine Translation (HP)
|
100% |
6209
106.9 IPS |
|
|
Machine Translation (Q)
|
98% |
7654
132.3 IPS |
