MacBook Pro (13-inch, 2022)
Geekbench ML Score
9694
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 25 2025 07:10 PM |
| Views | 8 |
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 | 3.37 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% |
2815
526.7 IPS |
|
|
Image Classification (F16)
|
100% |
10399
1.95 KIPS |
|
|
Image Classification (I8)
|
99% |
12115
2.27 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1498
25.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1960
32.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
1909
31.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
23094
28.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
93531
113.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
96509
116.9 IPS |
|
|
Object Detection (F32)
|
100% |
2712
202.5 IPS |
|
|
Object Detection (F16)
|
100% |
5570
415.8 IPS |
|
|
Object Detection (I8)
|
97% |
2762
206.2 IPS |
|
|
Face Detection (F32)
|
100% |
9353
111.2 IPS |
|
|
Face Detection (F16)
|
97% |
20355
242.0 IPS |
|
|
Face Detection (I8)
|
96% |
19998
237.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
16160
125.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
44937
348.5 IPS |
|
|
Depth Estimation (I8)
|
37% |
48843
378.8 IPS |
|
|
Style Transfer (F32)
|
100% |
40846
53.7 IPS |
|
|
Style Transfer (F16)
|
100% |
132413
174.2 IPS |
|
|
Style Transfer (I8)
|
100% |
137337
180.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6070
216.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
33687
1.20 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
35406
1.26 KIPS |
|
|
Text Classification (F32)
|
100% |
2108
3.03 KIPS |
|
|
Text Classification (F16)
|
100% |
3475
4.99 KIPS |
|
|
Text Classification (I8)
|
96% |
3463
4.98 KIPS |
|
|
Machine Translation (F32)
|
100% |
927
17.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1407
25.9 IPS |
|
|
Machine Translation (I8)
|
99% |
949
17.5 IPS |
