MacBook Pro (14-inch, 2023)
Geekbench ML Score
8718
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | May 08 2024 03:26 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.2.1 (Build 23C71) |
| Model | MacBook Pro (14-inch, 2023) |
| Model ID | Mac14,9 |
| Motherboard | Mac14,9 |
| CPU Information | |
|---|---|
| Name | Apple M2 Pro |
| Topology | 1 Processor, 10 Cores |
| Identifier | Apple M2 Pro |
| Base Frequency | 3.22 GHz |
| Cluster 1 | 6 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 | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
4855
908.4 IPS |
|
|
Image Classification (F16)
|
100% |
7125
1.33 KIPS |
|
|
Image Classification (I8)
|
99% |
7796
1.46 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1835
30.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1716
28.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
1709
28.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
34274
41.5 IPS |
|
|
Pose Estimation (F16)
|
100% |
82701
100.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
83014
100.5 IPS |
|
|
Object Detection (F32)
|
100% |
3065
228.8 IPS |
|
|
Object Detection (F16)
|
100% |
4088
305.2 IPS |
|
|
Object Detection (I8)
|
97% |
2952
220.4 IPS |
|
|
Face Detection (F32)
|
100% |
13438
159.8 IPS |
|
|
Face Detection (F16)
|
97% |
13474
160.2 IPS |
|
|
Face Detection (I8)
|
96% |
13640
162.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
23251
180.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
40089
310.9 IPS |
|
|
Depth Estimation (I8)
|
37% |
38990
302.4 IPS |
|
|
Style Transfer (F32)
|
100% |
63996
84.2 IPS |
|
|
Style Transfer (F16)
|
100% |
135711
178.5 IPS |
|
|
Style Transfer (I8)
|
100% |
133774
176.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7775
277.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
16886
603.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
16432
586.8 IPS |
|
|
Text Classification (F32)
|
100% |
586
842.0 IPS |
|
|
Text Classification (F16)
|
100% |
2782
4.00 KIPS |
|
|
Text Classification (I8)
|
96% |
2856
4.10 KIPS |
|
|
Machine Translation (F32)
|
100% |
774
14.2 IPS |
|
|
Machine Translation (F16)
|
100% |
2179
40.1 IPS |
|
|
Machine Translation (I8)
|
99% |
732
13.5 IPS |
