iPhone 15 Pro
Geekbench ML Score
6116
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 08 2024 10:12 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| 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% |
1278
239.2 IPS |
|
|
Image Classification (F16)
|
100% |
6229
1.17 KIPS |
|
|
Image Classification (I8)
|
99% |
6939
1.30 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1519
25.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1857
31.0 IPS |
|
|
Image Segmentation (I8)
|
100% |
1863
31.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
14878
18.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
84161
101.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
86322
104.5 IPS |
|
|
Object Detection (F32)
|
100% |
2403
179.4 IPS |
|
|
Object Detection (F16)
|
100% |
3816
284.9 IPS |
|
|
Object Detection (I8)
|
97% |
1945
145.2 IPS |
|
|
Face Detection (F32)
|
100% |
6229
74.1 IPS |
|
|
Face Detection (F16)
|
97% |
10696
127.2 IPS |
|
|
Face Detection (I8)
|
96% |
10480
124.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
12440
96.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
37852
293.5 IPS |
|
|
Depth Estimation (I8)
|
37% |
45389
352.0 IPS |
|
|
Style Transfer (F32)
|
100% |
29703
39.1 IPS |
|
|
Style Transfer (F16)
|
100% |
123803
162.9 IPS |
|
|
Style Transfer (I8)
|
100% |
122209
160.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6299
225.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
17773
634.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
17467
623.8 IPS |
|
|
Text Classification (F32)
|
100% |
456
655.3 IPS |
|
|
Text Classification (F16)
|
100% |
488
701.5 IPS |
|
|
Text Classification (I8)
|
96% |
307
440.6 IPS |
|
|
Machine Translation (F32)
|
100% |
749
13.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1551
28.6 IPS |
|
|
Machine Translation (I8)
|
99% |
676
12.4 IPS |
