iPhone 15 Pro Max
Geekbench AI Score
3843
Single Precision Score
24910
Half Precision Score
34437
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | November 06 2024 02:40 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% |
1668
310.2 IPS |
|
|
Image Classification (HP)
|
100% |
11437
2.13 KIPS |
|
|
Image Classification (Q)
|
97% |
15004
2.80 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1580
25.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
15662
253.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
20881
338.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
7303
8.52 IPS |
|
|
Pose Estimation (HP)
|
100% |
103051
120.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
202652
237.5 IPS |
|
|
Object Detection (SP)
|
100% |
1743
138.2 IPS |
|
|
Object Detection (HP)
|
100% |
13731
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
18950
1.51 KIPS |
|
|
Face Detection (SP)
|
100% |
3170
37.7 IPS |
|
|
Face Detection (HP)
|
100% |
34401
408.8 IPS |
|
|
Face Detection (Q)
|
100% |
49983
593.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
6928
53.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
78610
605.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
127190
994.4 IPS |
|
|
Style Transfer (SP)
|
100% |
20197
26.0 IPS |
|
|
Style Transfer (HP)
|
100% |
202813
260.7 IPS |
|
|
Style Transfer (Q)
|
96% |
244638
315.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4785
176.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34019
1.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
55067
2.03 KIPS |
|
|
Text Classification (SP)
|
100% |
3206
4.28 KIPS |
|
|
Text Classification (HP)
|
100% |
3121
4.17 KIPS |
|
|
Text Classification (Q)
|
93% |
3129
4.20 KIPS |
|
|
Machine Translation (SP)
|
100% |
3080
53.1 IPS |
|
|
Machine Translation (HP)
|
100% |
6233
107.4 IPS |
|
|
Machine Translation (Q)
|
98% |
7277
125.7 IPS |
