MacBook Pro (13-inch, 2022)
Geekbench ML Score
2179
Core ML CPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | May 08 2024 12:28 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.4.1 (Build 23E224) |
| Model | MacBook Pro (13-inch, 2022) |
| Model ID | Mac14,7 |
| Motherboard | Mac14,7 |
| CPU Information | |
|---|---|
| Name | Apple M2 |
| Topology | 1 Processor, 8 Cores |
| Identifier | Apple M2 |
| Base Frequency | 1.95 GHz |
| Cluster 1 | 4 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
917
171.6 IPS |
|
|
Image Classification (F16)
|
100% |
1125
210.5 IPS |
|
|
Image Classification (I8)
|
99% |
1125
210.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
565
9.44 IPS |
|
|
Image Segmentation (F16)
|
100% |
547
9.14 IPS |
|
|
Image Segmentation (I8)
|
100% |
544
9.09 IPS |
|
|
Pose Estimation (F32)
|
100% |
3636
4.40 IPS |
|
|
Pose Estimation (F16)
|
100% |
8721
10.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
8724
10.6 IPS |
|
|
Object Detection (F32)
|
100% |
938
70.0 IPS |
|
|
Object Detection (F16)
|
100% |
1227
91.6 IPS |
|
|
Object Detection (I8)
|
97% |
944
70.5 IPS |
|
|
Face Detection (F32)
|
100% |
1857
22.1 IPS |
|
|
Face Detection (F16)
|
97% |
2661
31.6 IPS |
|
|
Face Detection (I8)
|
97% |
2622
31.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
3404
26.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
5276
40.9 IPS |
|
|
Depth Estimation (I8)
|
99% |
5283
41.0 IPS |
|
|
Style Transfer (F32)
|
100% |
10454
13.8 IPS |
|
|
Style Transfer (F16)
|
100% |
16106
21.2 IPS |
|
|
Style Transfer (I8)
|
100% |
16108
21.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2411
86.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
3189
113.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
3195
114.1 IPS |
|
|
Text Classification (F32)
|
100% |
1374
1.98 KIPS |
|
|
Text Classification (F16)
|
100% |
1908
2.74 KIPS |
|
|
Text Classification (I8)
|
96% |
1913
2.75 KIPS |
|
|
Machine Translation (F32)
|
100% |
799
14.7 IPS |
|
|
Machine Translation (F16)
|
100% |
931
17.1 IPS |
|
|
Machine Translation (I8)
|
99% |
795
14.6 IPS |
