MacBook Pro (16-inch, 2023)
Geekbench ML Score
9552
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 17 2024 03:45 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.6.1 (Build 23G93) |
| 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 | 3.67 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 | 96.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
5876
1.10 KIPS |
|
|
Image Classification (F16)
|
100% |
7161
1.34 KIPS |
|
|
Image Classification (I8)
|
99% |
7946
1.49 KIPS |
|
|
Image Segmentation (F32)
|
100% |
2271
37.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1900
31.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
1928
32.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
72515
87.8 IPS |
|
|
Pose Estimation (F16)
|
100% |
78266
94.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
85256
103.2 IPS |
|
|
Object Detection (F32)
|
100% |
3741
279.3 IPS |
|
|
Object Detection (F16)
|
100% |
4354
325.1 IPS |
|
|
Object Detection (I8)
|
97% |
3541
264.4 IPS |
|
|
Face Detection (F32)
|
100% |
20577
244.7 IPS |
|
|
Face Detection (F16)
|
97% |
11389
135.4 IPS |
|
|
Face Detection (I8)
|
96% |
10917
129.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
29883
231.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
36907
286.2 IPS |
|
|
Depth Estimation (I8)
|
37% |
39472
306.1 IPS |
|
|
Style Transfer (F32)
|
100% |
121788
160.2 IPS |
|
|
Style Transfer (F16)
|
100% |
137547
180.9 IPS |
|
|
Style Transfer (I8)
|
100% |
131645
173.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
12394
442.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
17980
642.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
17869
638.1 IPS |
|
|
Text Classification (F32)
|
100% |
419
602.2 IPS |
|
|
Text Classification (F16)
|
100% |
2533
3.64 KIPS |
|
|
Text Classification (I8)
|
96% |
2573
3.70 KIPS |
|
|
Machine Translation (F32)
|
100% |
1005
18.5 IPS |
|
|
Machine Translation (F16)
|
100% |
1402
25.8 IPS |
|
|
Machine Translation (I8)
|
99% |
867
16.0 IPS |
