MacBook Pro (13-inch, 2022)
Geekbench ML Score
8918
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 26 2025 06:56 PM |
| Views | 9 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.0 (Build 25A5349a) |
| 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% |
3284
614.5 IPS |
|
|
Image Classification (F16)
|
100% |
10241
1.92 KIPS |
|
|
Image Classification (I8)
|
99% |
11265
2.11 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1279
21.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1834
30.6 IPS |
|
|
Image Segmentation (I8)
|
100% |
1475
24.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
22630
27.4 IPS |
|
|
Pose Estimation (F16)
|
100% |
94395
114.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
96891
117.3 IPS |
|
|
Object Detection (F32)
|
100% |
1561
116.5 IPS |
|
|
Object Detection (F16)
|
100% |
4324
322.8 IPS |
|
|
Object Detection (I8)
|
97% |
1521
113.6 IPS |
|
|
Face Detection (F32)
|
100% |
9110
108.3 IPS |
|
|
Face Detection (F16)
|
97% |
20369
242.2 IPS |
|
|
Face Detection (I8)
|
96% |
17546
208.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
15635
121.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
54900
425.8 IPS |
|
|
Depth Estimation (I8)
|
37% |
63792
494.7 IPS |
|
|
Style Transfer (F32)
|
100% |
39729
52.3 IPS |
|
|
Style Transfer (F16)
|
100% |
136678
179.8 IPS |
|
|
Style Transfer (I8)
|
100% |
124838
164.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5066
180.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
30597
1.09 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
33770
1.21 KIPS |
|
|
Text Classification (F32)
|
100% |
2070
2.97 KIPS |
|
|
Text Classification (F16)
|
100% |
3375
4.85 KIPS |
|
|
Text Classification (I8)
|
96% |
3359
4.83 KIPS |
|
|
Machine Translation (F32)
|
100% |
730
13.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1263
23.2 IPS |
|
|
Machine Translation (I8)
|
99% |
845
15.6 IPS |
