MacBook Pro (13-inch, 2022)
Geekbench ML Score
9573
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | January 13 2026 06:58 PM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.3 (Build 25D5101c) |
| 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% |
2925
547.4 IPS |
|
|
Image Classification (F16)
|
100% |
10360
1.94 KIPS |
|
|
Image Classification (I8)
|
99% |
10771
2.02 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1353
22.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
1658
27.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
1693
28.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
22230
26.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
94073
113.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
96642
117.0 IPS |
|
|
Object Detection (F32)
|
100% |
2490
185.9 IPS |
|
|
Object Detection (F16)
|
100% |
5219
389.6 IPS |
|
|
Object Detection (I8)
|
97% |
2502
186.8 IPS |
|
|
Face Detection (F32)
|
100% |
8861
105.4 IPS |
|
|
Face Detection (F16)
|
97% |
20066
238.6 IPS |
|
|
Face Detection (I8)
|
96% |
19426
231.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
10513
81.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
49287
382.2 IPS |
|
|
Depth Estimation (I8)
|
37% |
50359
390.5 IPS |
|
|
Style Transfer (F32)
|
100% |
38545
50.7 IPS |
|
|
Style Transfer (F16)
|
100% |
136462
179.5 IPS |
|
|
Style Transfer (I8)
|
100% |
143322
188.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
9465
338.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
35889
1.28 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
34611
1.24 KIPS |
|
|
Text Classification (F32)
|
100% |
2116
3.04 KIPS |
|
|
Text Classification (F16)
|
100% |
3544
5.09 KIPS |
|
|
Text Classification (I8)
|
96% |
3573
5.13 KIPS |
|
|
Machine Translation (F32)
|
100% |
1055
19.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1413
26.0 IPS |
|
|
Machine Translation (I8)
|
99% |
1042
19.2 IPS |
