MacBook Pro (16-inch, Nov 2023)
Geekbench ML Score
9522
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 16 2024 07:44 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.6.1 (Build 23G93) |
| Model | MacBook Pro (16-inch, Nov 2023) |
| Model ID | Mac15,9 |
| Motherboard | Mac15,9 |
| 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 | 48.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
6934
1.30 KIPS |
|
|
Image Classification (F16)
|
100% |
7275
1.36 KIPS |
|
|
Image Classification (I8)
|
99% |
6708
1.26 KIPS |
|
|
Image Segmentation (F32)
|
100% |
2939
49.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
3022
50.5 IPS |
|
|
Image Segmentation (I8)
|
100% |
2959
49.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
84563
102.4 IPS |
|
|
Pose Estimation (F16)
|
100% |
61234
74.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
58146
70.4 IPS |
|
|
Object Detection (F32)
|
100% |
5058
377.6 IPS |
|
|
Object Detection (F16)
|
100% |
5311
396.5 IPS |
|
|
Object Detection (I8)
|
97% |
5020
374.8 IPS |
|
|
Face Detection (F32)
|
100% |
24401
290.1 IPS |
|
|
Face Detection (F16)
|
98% |
26295
312.7 IPS |
|
|
Face Detection (I8)
|
97% |
24326
289.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
33971
263.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
36293
281.5 IPS |
|
|
Depth Estimation (I8)
|
37% |
36727
284.8 IPS |
|
|
Style Transfer (F32)
|
100% |
109421
143.9 IPS |
|
|
Style Transfer (F16)
|
100% |
119095
156.7 IPS |
|
|
Style Transfer (I8)
|
100% |
123397
162.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
12114
432.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
8231
294.0 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
13326
475.9 IPS |
|
|
Text Classification (F32)
|
100% |
1244
1.79 KIPS |
|
|
Text Classification (F16)
|
100% |
859
1.23 KIPS |
|
|
Text Classification (I8)
|
96% |
766
1.10 KIPS |
|
|
Machine Translation (F32)
|
100% |
811
14.9 IPS |
|
|
Machine Translation (F16)
|
100% |
825
15.2 IPS |
|
|
Machine Translation (I8)
|
99% |
771
14.2 IPS |
