MacBook Pro (13-inch, 2022)
Geekbench ML Score
9184
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | February 13 2025 08:33 PM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 15.3.1 (Build 24D70) |
| 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 | 3.29 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% |
3448
645.3 IPS |
|
|
Image Classification (F16)
|
100% |
9747
1.82 KIPS |
|
|
Image Classification (I8)
|
99% |
11188
2.09 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1061
17.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1639
27.4 IPS |
|
|
Image Segmentation (I8)
|
100% |
1946
32.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
22842
27.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
96143
116.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
96297
116.6 IPS |
|
|
Object Detection (F32)
|
100% |
2074
154.9 IPS |
|
|
Object Detection (F16)
|
100% |
6019
449.4 IPS |
|
|
Object Detection (I8)
|
97% |
2256
168.4 IPS |
|
|
Face Detection (F32)
|
100% |
8932
106.2 IPS |
|
|
Face Detection (F16)
|
97% |
17383
206.7 IPS |
|
|
Face Detection (I8)
|
96% |
19873
236.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
15591
120.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
45978
356.6 IPS |
|
|
Depth Estimation (I8)
|
37% |
47473
368.2 IPS |
|
|
Style Transfer (F32)
|
100% |
40741
53.6 IPS |
|
|
Style Transfer (F16)
|
100% |
147938
194.6 IPS |
|
|
Style Transfer (I8)
|
100% |
114029
150.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7431
265.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
31925
1.14 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
33618
1.20 KIPS |
|
|
Text Classification (F32)
|
100% |
2038
2.93 KIPS |
|
|
Text Classification (F16)
|
100% |
3442
4.95 KIPS |
|
|
Text Classification (I8)
|
96% |
3463
4.98 KIPS |
|
|
Machine Translation (F32)
|
100% |
725
13.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1411
26.0 IPS |
|
|
Machine Translation (I8)
|
99% |
719
13.2 IPS |
