iPhone 15 Pro Max
Geekbench AI Score
4004
Single Precision Score
24927
Half Precision Score
35325
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | December 24 2024 12:22 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.2 |
| 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% |
1724
320.6 IPS |
|
|
Image Classification (HP)
|
100% |
11287
2.10 KIPS |
|
|
Image Classification (Q)
|
97% |
15482
2.89 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1598
25.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
15754
255.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
20907
338.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
8389
9.79 IPS |
|
|
Pose Estimation (HP)
|
100% |
105985
123.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
203233
238.2 IPS |
|
|
Object Detection (SP)
|
100% |
1825
144.7 IPS |
|
|
Object Detection (HP)
|
100% |
13728
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
18988
1.52 KIPS |
|
|
Face Detection (SP)
|
100% |
3189
37.9 IPS |
|
|
Face Detection (HP)
|
100% |
34383
408.5 IPS |
|
|
Face Detection (Q)
|
100% |
50513
600.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
7156
55.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
78466
604.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
128628
1.01 KIPS |
|
|
Style Transfer (SP)
|
100% |
21666
27.9 IPS |
|
|
Style Transfer (HP)
|
100% |
202422
260.2 IPS |
|
|
Style Transfer (Q)
|
96% |
245132
316.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5115
188.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33841
1.25 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
60240
2.22 KIPS |
|
|
Text Classification (SP)
|
100% |
3202
4.27 KIPS |
|
|
Text Classification (HP)
|
100% |
3107
4.15 KIPS |
|
|
Text Classification (Q)
|
93% |
3418
4.59 KIPS |
|
|
Machine Translation (SP)
|
100% |
3104
53.5 IPS |
|
|
Machine Translation (HP)
|
100% |
6237
107.4 IPS |
|
|
Machine Translation (Q)
|
98% |
7387
127.7 IPS |
