iPhone 15 Pro Max
Geekbench AI Score
3950
Single Precision Score
24426
Half Precision Score
34550
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | December 25 2024 10:33 PM |
| Views | 2 |
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% |
1698
315.9 IPS |
|
|
Image Classification (HP)
|
100% |
11476
2.13 KIPS |
|
|
Image Classification (Q)
|
97% |
15089
2.82 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1601
26.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
15849
256.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
20675
335.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
7956
9.28 IPS |
|
|
Pose Estimation (HP)
|
100% |
106457
124.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
202895
237.8 IPS |
|
|
Object Detection (SP)
|
100% |
1812
143.7 IPS |
|
|
Object Detection (HP)
|
100% |
13730
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
18995
1.52 KIPS |
|
|
Face Detection (SP)
|
100% |
3152
37.5 IPS |
|
|
Face Detection (HP)
|
100% |
33695
400.4 IPS |
|
|
Face Detection (Q)
|
100% |
50057
594.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
7060
54.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
78635
605.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
126184
986.6 IPS |
|
|
Style Transfer (SP)
|
100% |
21318
27.4 IPS |
|
|
Style Transfer (HP)
|
100% |
202118
259.8 IPS |
|
|
Style Transfer (Q)
|
96% |
247091
318.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5040
186.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33690
1.24 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
58615
2.16 KIPS |
|
|
Text Classification (SP)
|
100% |
3192
4.26 KIPS |
|
|
Text Classification (HP)
|
100% |
2587
3.45 KIPS |
|
|
Text Classification (Q)
|
93% |
3038
4.08 KIPS |
|
|
Machine Translation (SP)
|
100% |
3097
53.3 IPS |
|
|
Machine Translation (HP)
|
100% |
6095
105.0 IPS |
|
|
Machine Translation (Q)
|
98% |
7254
125.4 IPS |
