iPhone 15 Pro Max
Geekbench AI Score
3900
Single Precision Score
25205
Half Precision Score
35158
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | November 07 2024 07:17 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| 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% |
1710
317.9 IPS |
|
|
Image Classification (HP)
|
100% |
11017
2.05 KIPS |
|
|
Image Classification (Q)
|
97% |
15494
2.89 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1611
26.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
15980
259.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
20775
336.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
7408
8.64 IPS |
|
|
Pose Estimation (HP)
|
100% |
104606
122.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
202881
237.8 IPS |
|
|
Object Detection (SP)
|
100% |
1779
141.1 IPS |
|
|
Object Detection (HP)
|
100% |
13807
1.10 KIPS |
|
|
Object Detection (Q)
|
91% |
19281
1.54 KIPS |
|
|
Face Detection (SP)
|
100% |
3204
38.1 IPS |
|
|
Face Detection (HP)
|
100% |
34304
407.6 IPS |
|
|
Face Detection (Q)
|
100% |
51567
612.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
7085
54.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
78774
606.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
127650
998.0 IPS |
|
|
Style Transfer (SP)
|
100% |
20490
26.3 IPS |
|
|
Style Transfer (HP)
|
100% |
201989
259.7 IPS |
|
|
Style Transfer (Q)
|
96% |
248689
320.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4852
179.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34276
1.27 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
56303
2.08 KIPS |
|
|
Text Classification (SP)
|
100% |
3200
4.27 KIPS |
|
|
Text Classification (HP)
|
100% |
3204
4.28 KIPS |
|
|
Text Classification (Q)
|
93% |
3233
4.34 KIPS |
|
|
Machine Translation (SP)
|
100% |
3105
53.5 IPS |
|
|
Machine Translation (HP)
|
100% |
6792
117.0 IPS |
|
|
Machine Translation (Q)
|
98% |
7691
132.9 IPS |
