iPhone 15 Pro Max
Geekbench AI Score
4023
Single Precision Score
24056
Half Precision Score
32903
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | November 24 2024 08:28 PM |
| 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% |
1636
304.3 IPS |
|
|
Image Classification (HP)
|
100% |
11418
2.12 KIPS |
|
|
Image Classification (Q)
|
97% |
15358
2.87 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1635
26.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
15509
251.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
20946
339.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
8271
9.65 IPS |
|
|
Pose Estimation (HP)
|
100% |
107276
125.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
204760
240.0 IPS |
|
|
Object Detection (SP)
|
100% |
1827
144.9 IPS |
|
|
Object Detection (HP)
|
100% |
13566
1.08 KIPS |
|
|
Object Detection (Q)
|
91% |
18815
1.50 KIPS |
|
|
Face Detection (SP)
|
100% |
3181
37.8 IPS |
|
|
Face Detection (HP)
|
100% |
33367
396.5 IPS |
|
|
Face Detection (Q)
|
100% |
51136
607.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
7148
55.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
80295
618.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
128700
1.01 KIPS |
|
|
Style Transfer (SP)
|
100% |
22076
28.4 IPS |
|
|
Style Transfer (HP)
|
100% |
202304
260.1 IPS |
|
|
Style Transfer (Q)
|
96% |
249401
321.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5139
189.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
35781
1.32 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
59644
2.20 KIPS |
|
|
Text Classification (SP)
|
100% |
3253
4.34 KIPS |
|
|
Text Classification (HP)
|
100% |
1985
2.65 KIPS |
|
|
Text Classification (Q)
|
93% |
1690
2.27 KIPS |
|
|
Machine Translation (SP)
|
100% |
3275
56.4 IPS |
|
|
Machine Translation (HP)
|
100% |
6543
112.7 IPS |
|
|
Machine Translation (Q)
|
98% |
7253
125.3 IPS |
