MacBook Pro (16-inch, 2023)
Geekbench ML Score
8105
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| User | 46fy45 |
| Upload Date | January 06 2025 05:04 AM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 15.1 (Build 24B83) |
| Model | MacBook Pro (16-inch, 2023) |
| Model ID | Mac14,10 |
| Motherboard | Mac14,10 |
| CPU Information | |
|---|---|
| Name | Apple M2 Pro |
| Topology | 1 Processor, 12 Cores |
| Identifier | Apple M2 Pro |
| Base Frequency | 3.45 GHz |
| Cluster 1 | 8 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 | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
4663
872.6 IPS |
|
|
Image Classification (F16)
|
100% |
4576
856.4 IPS |
|
|
Image Classification (I8)
|
99% |
4851
907.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
1810
30.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
2033
33.9 IPS |
|
|
Image Segmentation (I8)
|
100% |
1994
33.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
41460
50.2 IPS |
|
|
Pose Estimation (F16)
|
100% |
43841
53.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
42800
51.8 IPS |
|
|
Object Detection (F32)
|
100% |
3316
247.5 IPS |
|
|
Object Detection (F16)
|
100% |
3328
248.5 IPS |
|
|
Object Detection (I8)
|
97% |
3237
241.7 IPS |
|
|
Face Detection (F32)
|
100% |
14065
167.2 IPS |
|
|
Face Detection (F16)
|
98% |
15005
178.4 IPS |
|
|
Face Detection (I8)
|
97% |
15106
179.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
24669
191.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
25408
197.0 IPS |
|
|
Depth Estimation (I8)
|
99% |
23606
183.1 IPS |
|
|
Style Transfer (F32)
|
100% |
70767
93.1 IPS |
|
|
Style Transfer (F16)
|
100% |
80083
105.3 IPS |
|
|
Style Transfer (I8)
|
100% |
79490
104.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
11661
416.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
10966
391.6 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
12767
455.9 IPS |
|
|
Text Classification (F32)
|
100% |
2077
2.98 KIPS |
|
|
Text Classification (F16)
|
100% |
3659
5.26 KIPS |
|
|
Text Classification (I8)
|
96% |
3677
5.28 KIPS |
|
|
Machine Translation (F32)
|
100% |
970
17.9 IPS |
|
|
Machine Translation (F16)
|
100% |
974
17.9 IPS |
|
|
Machine Translation (I8)
|
99% |
947
17.4 IPS |
