MacBook Pro (16-inch, Nov 2023)
Geekbench ML Score
10128
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 15 2024 06:08 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.6 (Build 23G80) |
| 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 | 64.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
6775
1.27 KIPS |
|
|
Image Classification (F16)
|
100% |
7137
1.34 KIPS |
|
|
Image Classification (I8)
|
99% |
6559
1.23 KIPS |
|
|
Image Segmentation (F32)
|
100% |
3059
51.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
2815
47.0 IPS |
|
|
Image Segmentation (I8)
|
100% |
2813
47.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
84700
102.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
87735
106.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
84557
102.4 IPS |
|
|
Object Detection (F32)
|
100% |
5147
384.2 IPS |
|
|
Object Detection (F16)
|
100% |
5248
391.8 IPS |
|
|
Object Detection (I8)
|
97% |
5034
375.8 IPS |
|
|
Face Detection (F32)
|
100% |
24246
288.3 IPS |
|
|
Face Detection (F16)
|
98% |
25592
304.3 IPS |
|
|
Face Detection (I8)
|
97% |
24805
294.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
35948
278.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
38943
302.0 IPS |
|
|
Depth Estimation (I8)
|
37% |
38337
297.3 IPS |
|
|
Style Transfer (F32)
|
100% |
158038
207.9 IPS |
|
|
Style Transfer (F16)
|
100% |
170051
223.7 IPS |
|
|
Style Transfer (I8)
|
100% |
173637
228.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
12345
440.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
10635
379.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
10002
357.2 IPS |
|
|
Text Classification (F32)
|
100% |
727
1.05 KIPS |
|
|
Text Classification (F16)
|
100% |
727
1.05 KIPS |
|
|
Text Classification (I8)
|
96% |
726
1.04 KIPS |
|
|
Machine Translation (F32)
|
100% |
1075
19.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1072
19.7 IPS |
|
|
Machine Translation (I8)
|
99% |
997
18.3 IPS |
