MacBook Pro (16-inch, Nov 2023)
Geekbench ML Score
9216
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 16 2024 07:51 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 | 128.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
6832
1.28 KIPS |
|
|
Image Classification (F16)
|
100% |
7145
1.34 KIPS |
|
|
Image Classification (I8)
|
99% |
6638
1.24 KIPS |
|
|
Image Segmentation (F32)
|
100% |
2959
49.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
2917
48.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
2889
48.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
58748
71.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
87365
105.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
84442
102.3 IPS |
|
|
Object Detection (F32)
|
100% |
5060
377.8 IPS |
|
|
Object Detection (F16)
|
100% |
5260
392.7 IPS |
|
|
Object Detection (I8)
|
97% |
5040
376.2 IPS |
|
|
Face Detection (F32)
|
100% |
23002
273.5 IPS |
|
|
Face Detection (F16)
|
98% |
25392
301.9 IPS |
|
|
Face Detection (I8)
|
97% |
24766
294.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
35433
274.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
37811
293.2 IPS |
|
|
Depth Estimation (I8)
|
37% |
37919
294.1 IPS |
|
|
Style Transfer (F32)
|
100% |
112811
148.4 IPS |
|
|
Style Transfer (F16)
|
100% |
116450
153.2 IPS |
|
|
Style Transfer (I8)
|
100% |
120810
158.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
11875
424.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
13139
469.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
12726
454.5 IPS |
|
|
Text Classification (F32)
|
100% |
456
655.2 IPS |
|
|
Text Classification (F16)
|
100% |
564
810.8 IPS |
|
|
Text Classification (I8)
|
96% |
581
835.3 IPS |
|
|
Machine Translation (F32)
|
100% |
782
14.4 IPS |
|
|
Machine Translation (F16)
|
100% |
815
15.0 IPS |
|
|
Machine Translation (I8)
|
99% |
836
15.4 IPS |
