MacBook Pro (13-inch, 2022)
Geekbench ML Score
10502
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | March 08 2026 06:55 PM |
| Views | 9 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.4 (Build 25E5223i) |
| 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 | 3.45 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% |
3331
623.4 IPS |
|
|
Image Classification (F16)
|
100% |
10644
1.99 KIPS |
|
|
Image Classification (I8)
|
99% |
11461
2.14 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1396
23.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1868
31.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
2053
34.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
23157
28.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
93497
113.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
96683
117.1 IPS |
|
|
Object Detection (F32)
|
100% |
2769
206.8 IPS |
|
|
Object Detection (F16)
|
100% |
5521
412.1 IPS |
|
|
Object Detection (I8)
|
97% |
2851
212.8 IPS |
|
|
Face Detection (F32)
|
100% |
9436
112.2 IPS |
|
|
Face Detection (F16)
|
98% |
20684
245.9 IPS |
|
|
Face Detection (I8)
|
97% |
20525
244.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
15766
122.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
54522
422.8 IPS |
|
|
Depth Estimation (I8)
|
37% |
48047
372.6 IPS |
|
|
Style Transfer (F32)
|
100% |
39396
51.8 IPS |
|
|
Style Transfer (F16)
|
100% |
140488
184.8 IPS |
|
|
Style Transfer (I8)
|
100% |
151262
199.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7192
256.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
35904
1.28 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
34205
1.22 KIPS |
|
|
Text Classification (F32)
|
100% |
3809
5.47 KIPS |
|
|
Text Classification (F16)
|
100% |
5994
8.61 KIPS |
|
|
Text Classification (I8)
|
96% |
5589
8.03 KIPS |
|
|
Machine Translation (F32)
|
100% |
992
18.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1340
24.7 IPS |
|
|
Machine Translation (I8)
|
99% |
1058
19.5 IPS |
