MacBook Pro (13-inch, 2022)
Geekbench ML Score
9653
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 06 2025 05:58 PM |
| Views | 7 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.0 (Build 25A5327h) |
| 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 | 3.48 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% |
3485
652.2 IPS |
|
|
Image Classification (F16)
|
100% |
10674
2.00 KIPS |
|
|
Image Classification (I8)
|
99% |
11917
2.23 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1407
23.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
1680
28.1 IPS |
|
|
Image Segmentation (I8)
|
100% |
1613
26.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
21872
26.5 IPS |
|
|
Pose Estimation (F16)
|
100% |
88213
106.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
83232
100.8 IPS |
|
|
Object Detection (F32)
|
100% |
2665
198.9 IPS |
|
|
Object Detection (F16)
|
100% |
5447
406.6 IPS |
|
|
Object Detection (I8)
|
97% |
2005
149.7 IPS |
|
|
Face Detection (F32)
|
100% |
9053
107.6 IPS |
|
|
Face Detection (F16)
|
97% |
17850
212.2 IPS |
|
|
Face Detection (I8)
|
96% |
17717
210.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
15625
121.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
64296
498.6 IPS |
|
|
Depth Estimation (I8)
|
37% |
46546
361.0 IPS |
|
|
Style Transfer (F32)
|
100% |
34773
45.7 IPS |
|
|
Style Transfer (F16)
|
100% |
141873
186.6 IPS |
|
|
Style Transfer (I8)
|
100% |
136317
179.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
8607
307.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
34427
1.23 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
36846
1.32 KIPS |
|
|
Text Classification (F32)
|
100% |
2122
3.05 KIPS |
|
|
Text Classification (F16)
|
100% |
3513
5.05 KIPS |
|
|
Text Classification (I8)
|
96% |
3502
5.03 KIPS |
|
|
Machine Translation (F32)
|
100% |
1096
20.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1429
26.3 IPS |
|
|
Machine Translation (I8)
|
99% |
1093
20.1 IPS |
