MacBook Pro (13-inch, 2022)
Geekbench ML Score
9293
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | January 04 2026 05:16 PM |
| Views | 12 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.3 (Build 25D5087f) |
| 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 | 3.30 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% |
2031
380.1 IPS |
|
|
Image Classification (F16)
|
100% |
11212
2.10 KIPS |
|
|
Image Classification (I8)
|
99% |
11580
2.17 KIPS |
|
|
Image Segmentation (F32)
|
100% |
904
15.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
1834
30.6 IPS |
|
|
Image Segmentation (I8)
|
100% |
1541
25.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
22832
27.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
92509
112.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
96603
117.0 IPS |
|
|
Object Detection (F32)
|
100% |
2163
161.5 IPS |
|
|
Object Detection (F16)
|
100% |
5062
377.9 IPS |
|
|
Object Detection (I8)
|
97% |
2544
189.9 IPS |
|
|
Face Detection (F32)
|
100% |
9564
113.7 IPS |
|
|
Face Detection (F16)
|
97% |
19636
233.5 IPS |
|
|
Face Detection (I8)
|
96% |
19152
227.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
10283
79.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
61986
480.7 IPS |
|
|
Depth Estimation (I8)
|
37% |
49101
380.8 IPS |
|
|
Style Transfer (F32)
|
100% |
40514
53.3 IPS |
|
|
Style Transfer (F16)
|
100% |
146918
193.3 IPS |
|
|
Style Transfer (I8)
|
100% |
150051
197.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7222
257.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
36182
1.29 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
34960
1.25 KIPS |
|
|
Text Classification (F32)
|
100% |
2103
3.02 KIPS |
|
|
Text Classification (F16)
|
100% |
3474
4.99 KIPS |
|
|
Text Classification (I8)
|
96% |
3475
4.99 KIPS |
|
|
Machine Translation (F32)
|
100% |
904
16.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1394
25.7 IPS |
|
|
Machine Translation (I8)
|
99% |
987
18.2 IPS |
