iPhone 15 Pro Max
Geekbench AI Score
2724
Single Precision Score
13847
Half Precision Score
17825
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | September 17 2024 03:08 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| 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 | 7.44 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1456
270.7 IPS |
|
|
Image Classification (HP)
|
100% |
6271
1.17 KIPS |
|
|
Image Classification (Q)
|
97% |
7663
1.43 KIPS |
|
|
Image Segmentation (SP)
|
100% |
806
13.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
5184
84.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
9972
161.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
7370
8.60 IPS |
|
|
Pose Estimation (HP)
|
100% |
87653
102.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
152410
178.6 IPS |
|
|
Object Detection (SP)
|
100% |
1453
115.3 IPS |
|
|
Object Detection (HP)
|
100% |
8182
649.0 IPS |
|
|
Object Detection (Q)
|
93% |
9983
796.6 IPS |
|
|
Face Detection (SP)
|
100% |
2250
26.7 IPS |
|
|
Face Detection (HP)
|
100% |
11282
134.1 IPS |
|
|
Face Detection (Q)
|
100% |
13156
156.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
4703
36.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
42323
326.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
57997
453.4 IPS |
|
|
Style Transfer (SP)
|
100% |
12416
16.0 IPS |
|
|
Style Transfer (HP)
|
100% |
128104
164.7 IPS |
|
|
Style Transfer (Q)
|
96% |
137878
177.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3922
144.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
18466
681.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
26365
973.5 IPS |
|
|
Text Classification (SP)
|
100% |
1816
2.42 KIPS |
|
|
Text Classification (HP)
|
71% |
3822
5.50 KIPS |
|
|
Text Classification (Q)
|
69% |
3883
5.69 KIPS |
|
|
Machine Translation (SP)
|
100% |
1915
33.0 IPS |
|
|
Machine Translation (HP)
|
100% |
2575
44.4 IPS |
|
|
Machine Translation (Q)
|
98% |
2586
44.7 IPS |
