MacBook Pro (16-inch, 2023)
Geekbench ML Score
8270
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | May 09 2024 08:42 AM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.4.1 (Build 23E224) |
| Model | MacBook Pro (16-inch, 2023) |
| Model ID | Mac14,6 |
| Motherboard | Mac14,6 |
| CPU Information | |
|---|---|
| Name | Apple M2 Max |
| Topology | 1 Processor, 12 Cores |
| Identifier | Apple M2 Max |
| Base Frequency | 3.65 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% |
5934
1.11 KIPS |
|
|
Image Classification (F16)
|
100% |
6078
1.14 KIPS |
|
|
Image Classification (I8)
|
99% |
5404
1.01 KIPS |
|
|
Image Segmentation (F32)
|
100% |
2303
38.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
2288
38.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
2229
37.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
73515
89.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
75628
91.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
73162
88.6 IPS |
|
|
Object Detection (F32)
|
100% |
3738
279.1 IPS |
|
|
Object Detection (F16)
|
100% |
3856
287.9 IPS |
|
|
Object Detection (I8)
|
97% |
3661
273.3 IPS |
|
|
Face Detection (F32)
|
100% |
20561
244.5 IPS |
|
|
Face Detection (F16)
|
98% |
20177
239.9 IPS |
|
|
Face Detection (I8)
|
97% |
19520
232.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
30654
237.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
31886
247.3 IPS |
|
|
Depth Estimation (I8)
|
37% |
30805
238.9 IPS |
|
|
Style Transfer (F32)
|
100% |
119310
156.9 IPS |
|
|
Style Transfer (F16)
|
100% |
128131
168.5 IPS |
|
|
Style Transfer (I8)
|
100% |
136681
179.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
8399
300.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
11332
404.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
10583
378.0 IPS |
|
|
Text Classification (F32)
|
100% |
481
691.8 IPS |
|
|
Text Classification (F16)
|
100% |
562
807.7 IPS |
|
|
Text Classification (I8)
|
96% |
686
985.7 IPS |
|
|
Machine Translation (F32)
|
100% |
938
17.3 IPS |
|
|
Machine Translation (F16)
|
100% |
913
16.8 IPS |
|
|
Machine Translation (I8)
|
99% |
839
15.4 IPS |
