MacBook Pro (13-inch, 2022)
Geekbench ML Score
9859
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | October 03 2025 06:57 PM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.1 (Build 25B5042k) |
| 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% |
3413
638.6 IPS |
|
|
Image Classification (F16)
|
100% |
9747
1.82 KIPS |
|
|
Image Classification (I8)
|
99% |
12206
2.28 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1542
25.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1827
30.5 IPS |
|
|
Image Segmentation (I8)
|
100% |
1802
30.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
22830
27.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
94543
114.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
90727
109.9 IPS |
|
|
Object Detection (F32)
|
100% |
2850
212.8 IPS |
|
|
Object Detection (F16)
|
100% |
5319
397.1 IPS |
|
|
Object Detection (I8)
|
97% |
2564
191.4 IPS |
|
|
Face Detection (F32)
|
100% |
9341
111.1 IPS |
|
|
Face Detection (F16)
|
97% |
16706
198.6 IPS |
|
|
Face Detection (I8)
|
96% |
20435
243.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
16591
128.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
63143
489.7 IPS |
|
|
Depth Estimation (I8)
|
37% |
49854
386.6 IPS |
|
|
Style Transfer (F32)
|
100% |
40686
53.5 IPS |
|
|
Style Transfer (F16)
|
100% |
149417
196.5 IPS |
|
|
Style Transfer (I8)
|
100% |
146906
193.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
9657
344.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
34166
1.22 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
30163
1.08 KIPS |
|
|
Text Classification (F32)
|
100% |
2034
2.92 KIPS |
|
|
Text Classification (F16)
|
100% |
3346
4.81 KIPS |
|
|
Text Classification (I8)
|
96% |
3224
4.63 KIPS |
|
|
Machine Translation (F32)
|
100% |
943
17.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1371
25.2 IPS |
|
|
Machine Translation (I8)
|
99% |
994
18.3 IPS |
