iPhone 15 Pro Max
Geekbench AI Score
3881
Single Precision Score
24468
Half Precision Score
34497
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | September 17 2024 02:57 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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% |
11067
2.06 KIPS |
|
|
Image Classification (Q)
|
97% |
15829
2.95 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1598
25.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
12843
208.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
16025
259.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
7597
8.86 IPS |
|
|
Pose Estimation (HP)
|
100% |
106359
124.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
204408
239.6 IPS |
|
|
Object Detection (SP)
|
100% |
1763
139.8 IPS |
|
|
Object Detection (HP)
|
100% |
13600
1.08 KIPS |
|
|
Object Detection (Q)
|
91% |
19188
1.53 KIPS |
|
|
Face Detection (SP)
|
100% |
3145
37.4 IPS |
|
|
Face Detection (HP)
|
100% |
34641
411.6 IPS |
|
|
Face Detection (Q)
|
100% |
49114
583.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
6981
53.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
78851
607.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
128672
1.01 KIPS |
|
|
Style Transfer (SP)
|
100% |
20288
26.1 IPS |
|
|
Style Transfer (HP)
|
100% |
206203
265.1 IPS |
|
|
Style Transfer (Q)
|
96% |
247245
319.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4749
175.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34044
1.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
59730
2.21 KIPS |
|
|
Text Classification (SP)
|
100% |
3229
4.31 KIPS |
|
|
Text Classification (HP)
|
100% |
3183
4.25 KIPS |
|
|
Text Classification (Q)
|
93% |
3387
4.55 KIPS |
|
|
Machine Translation (SP)
|
100% |
3246
55.9 IPS |
|
|
Machine Translation (HP)
|
100% |
6130
105.6 IPS |
|
|
Machine Translation (Q)
|
98% |
7590
131.2 IPS |
