iPhone 15 Pro
Geekbench ML Score
6010
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 16 2024 02:47 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5 |
| Model | iPhone 15 Pro |
| Model ID | iPhone16,1 |
| Motherboard | D83AP |
| 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 |
| L1 Instruction Cache | 128 KB x 1 |
| L1 Data Cache | 64.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 7.47 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1516
283.8 IPS |
|
|
Image Classification (F16)
|
100% |
6260
1.17 KIPS |
|
|
Image Classification (I8)
|
99% |
6815
1.28 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1452
24.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1879
31.4 IPS |
|
|
Image Segmentation (I8)
|
100% |
1886
31.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
14881
18.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
83594
101.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
85457
103.5 IPS |
|
|
Object Detection (F32)
|
100% |
1469
109.7 IPS |
|
|
Object Detection (F16)
|
100% |
4002
298.8 IPS |
|
|
Object Detection (I8)
|
97% |
1586
118.4 IPS |
|
|
Face Detection (F32)
|
100% |
6501
77.3 IPS |
|
|
Face Detection (F16)
|
97% |
10702
127.2 IPS |
|
|
Face Detection (I8)
|
96% |
10639
126.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
12448
96.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
38219
296.4 IPS |
|
|
Depth Estimation (I8)
|
37% |
40876
317.0 IPS |
|
|
Style Transfer (F32)
|
100% |
29635
39.0 IPS |
|
|
Style Transfer (F16)
|
100% |
122549
161.2 IPS |
|
|
Style Transfer (I8)
|
100% |
122016
160.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6581
235.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
17285
617.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
17988
642.4 IPS |
|
|
Text Classification (F32)
|
100% |
475
683.2 IPS |
|
|
Text Classification (F16)
|
100% |
490
704.8 IPS |
|
|
Text Classification (I8)
|
96% |
303
435.9 IPS |
|
|
Machine Translation (F32)
|
100% |
735
13.5 IPS |
|
|
Machine Translation (F16)
|
100% |
1545
28.4 IPS |
|
|
Machine Translation (I8)
|
99% |
677
12.5 IPS |
