iPhone 15 Pro Max
Geekbench AI Score
4056
Single Precision Score
24353
Half Precision Score
33506
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | September 17 2024 04:17 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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% |
1726
320.9 IPS |
|
|
Image Classification (HP)
|
100% |
10866
2.02 KIPS |
|
|
Image Classification (Q)
|
97% |
15255
2.85 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1615
26.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
12965
210.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
16001
259.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
8636
10.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
106850
124.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
204153
239.3 IPS |
|
|
Object Detection (SP)
|
100% |
1842
146.1 IPS |
|
|
Object Detection (HP)
|
100% |
13397
1.06 KIPS |
|
|
Object Detection (Q)
|
91% |
19017
1.52 KIPS |
|
|
Face Detection (SP)
|
100% |
3233
38.4 IPS |
|
|
Face Detection (HP)
|
100% |
34392
408.6 IPS |
|
|
Face Detection (Q)
|
100% |
49241
585.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
7330
56.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
78721
606.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
127961
1.00 KIPS |
|
|
Style Transfer (SP)
|
100% |
21971
28.2 IPS |
|
|
Style Transfer (HP)
|
100% |
203039
261.0 IPS |
|
|
Style Transfer (Q)
|
96% |
244778
315.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5197
191.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34785
1.28 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
54807
2.02 KIPS |
|
|
Text Classification (SP)
|
100% |
3199
4.27 KIPS |
|
|
Text Classification (HP)
|
100% |
3053
4.08 KIPS |
|
|
Text Classification (Q)
|
93% |
3035
4.07 KIPS |
|
|
Machine Translation (SP)
|
100% |
3143
54.1 IPS |
|
|
Machine Translation (HP)
|
100% |
6233
107.4 IPS |
|
|
Machine Translation (Q)
|
98% |
7335
126.8 IPS |
