MacBook Pro (14-inch, Nov 2023)
Geekbench ML Score
10321
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 16 2024 10:07 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.6.1 (Build 23G93) |
| Model | MacBook Pro (14-inch, Nov 2023) |
| Model ID | Mac15,8 |
| Motherboard | Mac15,8 |
| CPU Information | |
|---|---|
| Name | Apple M3 Max |
| Topology | 1 Processor, 16 Cores |
| Identifier | Apple M3 Max |
| Base Frequency | 4.05 GHz |
| Cluster 1 | 12 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 | 128.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
6770
1.27 KIPS |
|
|
Image Classification (F16)
|
100% |
7024
1.31 KIPS |
|
|
Image Classification (I8)
|
99% |
6580
1.23 KIPS |
|
|
Image Segmentation (F32)
|
100% |
3040
50.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
3034
50.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
3117
52.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
83839
101.5 IPS |
|
|
Pose Estimation (F16)
|
100% |
86623
104.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
84161
101.9 IPS |
|
|
Object Detection (F32)
|
100% |
5102
380.9 IPS |
|
|
Object Detection (F16)
|
100% |
5251
392.0 IPS |
|
|
Object Detection (I8)
|
97% |
5044
376.6 IPS |
|
|
Face Detection (F32)
|
100% |
24116
286.7 IPS |
|
|
Face Detection (F16)
|
98% |
26162
311.1 IPS |
|
|
Face Detection (I8)
|
97% |
22936
272.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
35785
277.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
37662
292.1 IPS |
|
|
Depth Estimation (I8)
|
37% |
37469
290.6 IPS |
|
|
Style Transfer (F32)
|
100% |
160180
210.7 IPS |
|
|
Style Transfer (F16)
|
100% |
174893
230.1 IPS |
|
|
Style Transfer (I8)
|
100% |
166509
219.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
17082
610.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
8996
321.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
9876
352.7 IPS |
|
|
Text Classification (F32)
|
100% |
1329
1.91 KIPS |
|
|
Text Classification (F16)
|
100% |
707
1.02 KIPS |
|
|
Text Classification (I8)
|
96% |
599
861.2 IPS |
|
|
Machine Translation (F32)
|
100% |
1090
20.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1083
19.9 IPS |
|
|
Machine Translation (I8)
|
99% |
1011
18.6 IPS |
