MacBook Pro (13-inch, 2022)
Geekbench ML Score
9711
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | April 29 2025 06:47 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 15.5 (Build 24F5068b) |
| 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 | 3.47 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 | 8.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
3275
612.8 IPS |
|
|
Image Classification (F16)
|
100% |
10019
1.87 KIPS |
|
|
Image Classification (I8)
|
99% |
11015
2.06 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1532
25.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
1957
32.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
1571
26.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
22975
27.8 IPS |
|
|
Pose Estimation (F16)
|
100% |
94484
114.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
96486
116.8 IPS |
|
|
Object Detection (F32)
|
100% |
2833
211.5 IPS |
|
|
Object Detection (F16)
|
100% |
5356
399.9 IPS |
|
|
Object Detection (I8)
|
97% |
1920
143.3 IPS |
|
|
Face Detection (F32)
|
100% |
8743
104.0 IPS |
|
|
Face Detection (F16)
|
97% |
20148
239.6 IPS |
|
|
Face Detection (I8)
|
96% |
19994
237.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
16660
129.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
50808
394.0 IPS |
|
|
Depth Estimation (I8)
|
37% |
50799
393.9 IPS |
|
|
Style Transfer (F32)
|
100% |
39757
52.3 IPS |
|
|
Style Transfer (F16)
|
100% |
148471
195.3 IPS |
|
|
Style Transfer (I8)
|
100% |
149406
196.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7465
266.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
33290
1.19 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
33459
1.19 KIPS |
|
|
Text Classification (F32)
|
100% |
2047
2.94 KIPS |
|
|
Text Classification (F16)
|
100% |
3387
4.87 KIPS |
|
|
Text Classification (I8)
|
96% |
3425
4.92 KIPS |
|
|
Machine Translation (F32)
|
100% |
1021
18.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1405
25.9 IPS |
|
|
Machine Translation (I8)
|
99% |
1058
19.5 IPS |
