iPhone 15 Pro Max
Geekbench AI Score
3911
Single Precision Score
6788
Half Precision Score
5535
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | MrV |
| Upload Date | November 08 2024 07:05 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| 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% |
1706
317.3 IPS |
|
|
Image Classification (HP)
|
100% |
2910
541.2 IPS |
|
|
Image Classification (Q)
|
96% |
2002
373.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1606
26.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2422
39.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
3082
50.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
8082
9.43 IPS |
|
|
Pose Estimation (HP)
|
100% |
16339
19.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
14231
16.7 IPS |
|
|
Object Detection (SP)
|
100% |
1767
140.1 IPS |
|
|
Object Detection (HP)
|
97% |
3327
264.8 IPS |
|
|
Object Detection (Q)
|
94% |
2352
187.5 IPS |
|
|
Face Detection (SP)
|
100% |
3139
37.3 IPS |
|
|
Face Detection (HP)
|
100% |
6745
80.1 IPS |
|
|
Face Detection (Q)
|
100% |
3836
45.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
6915
53.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
13359
103.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
9147
71.5 IPS |
|
|
Style Transfer (SP)
|
100% |
20924
26.9 IPS |
|
|
Style Transfer (HP)
|
100% |
32178
41.4 IPS |
|
|
Style Transfer (Q)
|
96% |
27207
35.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4895
180.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5866
216.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4349
160.6 IPS |
|
|
Text Classification (SP)
|
100% |
3105
4.14 KIPS |
|
|
Text Classification (HP)
|
100% |
5349
7.14 KIPS |
|
|
Text Classification (Q)
|
93% |
5266
7.07 KIPS |
|
|
Machine Translation (SP)
|
100% |
3105
53.5 IPS |
|
|
Machine Translation (HP)
|
98% |
5966
103.1 IPS |
|
|
Machine Translation (Q)
|
98% |
5978
103.3 IPS |
