MacBook Pro (16-inch, 2023)
Geekbench ML Score
8058
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 16 2024 08:39 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 15.1 (Build 24B5024e) |
| 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 | 3.47 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 | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
4603
861.3 IPS |
|
|
Image Classification (F16)
|
100% |
4792
896.7 IPS |
|
|
Image Classification (I8)
|
99% |
4383
820.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
2105
35.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
2110
35.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
2100
35.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
41218
49.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
43580
52.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
42223
51.1 IPS |
|
|
Object Detection (F32)
|
100% |
3242
242.0 IPS |
|
|
Object Detection (F16)
|
100% |
3337
249.1 IPS |
|
|
Object Detection (I8)
|
97% |
3086
230.4 IPS |
|
|
Face Detection (F32)
|
100% |
14582
173.4 IPS |
|
|
Face Detection (F16)
|
98% |
15205
180.8 IPS |
|
|
Face Detection (I8)
|
97% |
14907
177.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
24105
186.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
25496
197.7 IPS |
|
|
Depth Estimation (I8)
|
99% |
23430
181.7 IPS |
|
|
Style Transfer (F32)
|
100% |
73875
97.2 IPS |
|
|
Style Transfer (F16)
|
100% |
72559
95.4 IPS |
|
|
Style Transfer (I8)
|
100% |
77446
101.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
12210
436.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
10496
374.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
11759
419.9 IPS |
|
|
Text Classification (F32)
|
100% |
2102
3.02 KIPS |
|
|
Text Classification (F16)
|
100% |
3599
5.17 KIPS |
|
|
Text Classification (I8)
|
96% |
3569
5.13 KIPS |
|
|
Machine Translation (F32)
|
100% |
1004
18.5 IPS |
|
|
Machine Translation (F16)
|
100% |
1005
18.5 IPS |
|
|
Machine Translation (I8)
|
99% |
831
15.3 IPS |
