MacBook Pro (13-inch, 2022)
Geekbench ML Score
9580
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 18 2025 06:28 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.0 (Build 25A5338b) |
| 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 | 3.44 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% |
3142
588.0 IPS |
|
|
Image Classification (F16)
|
100% |
11091
2.08 KIPS |
|
|
Image Classification (I8)
|
99% |
12373
2.32 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1200
20.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1978
33.0 IPS |
|
|
Image Segmentation (I8)
|
100% |
1982
33.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
22904
27.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
85474
103.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
84513
102.3 IPS |
|
|
Object Detection (F32)
|
100% |
2084
155.6 IPS |
|
|
Object Detection (F16)
|
100% |
5614
419.1 IPS |
|
|
Object Detection (I8)
|
97% |
2768
206.7 IPS |
|
|
Face Detection (F32)
|
100% |
9280
110.3 IPS |
|
|
Face Detection (F16)
|
97% |
16828
200.1 IPS |
|
|
Face Detection (I8)
|
96% |
20257
240.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
15906
123.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
46519
360.8 IPS |
|
|
Depth Estimation (I8)
|
37% |
46305
359.1 IPS |
|
|
Style Transfer (F32)
|
100% |
34200
45.0 IPS |
|
|
Style Transfer (F16)
|
100% |
142763
187.8 IPS |
|
|
Style Transfer (I8)
|
100% |
150904
198.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7221
257.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
34363
1.23 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
34878
1.25 KIPS |
|
|
Text Classification (F32)
|
100% |
2113
3.04 KIPS |
|
|
Text Classification (F16)
|
100% |
3528
5.07 KIPS |
|
|
Text Classification (I8)
|
96% |
3545
5.10 KIPS |
|
|
Machine Translation (F32)
|
100% |
1099
20.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1422
26.2 IPS |
|
|
Machine Translation (I8)
|
99% |
890
16.4 IPS |
